Making the switch from Infosys to a product company or Global Capability Center is one of the most frequently attempted and most frequently botched career transitions in Indian technology. The desire to make the move is almost universal among ambitious engineers who have spent a few years in IT services delivery. The actual successful execution of that move is far less common - not because the candidates lack potential, but because most of them misunderstand what the transition actually requires, prepare for the wrong things in the wrong order, and approach the external job market with a services-company mindset that product company interviewers immediately identify and penalise.

Infosys to Product Company Switch Guide

This guide is the transition playbook that the majority of engineers attempting this switch never find in one place. It covers the honest diagnosis of what is actually different between IT services and product engineering environments, the specific skill gaps that most services-company engineers carry, how to close those gaps in a structured timeline, how to reframe a services resume into language that product companies understand and value, and how to prepare for the interview formats that are categorically different from anything Infosys’s internal processes have trained you for. It also covers the GCC option, which is both a genuine alternative to FAANG-tier product companies and a stepping stone that many engineers underestimate. Read every section - the transition is a system, and shortcutting any component degrades the whole.

Table of Contents

  1. Why Engineers Leave Infosys for Product Companies and GCCs
  2. Understanding the Product Company vs IT Services vs GCC Distinction
  3. The Skill Gap: What Infosys Builds and What It Does Not
  4. Data Structures and Algorithms: The Non-Negotiable Gap
  5. System Design: The Mid-Career Differentiator
  6. Domain and Technology Stack Depth
  7. Building Your Resume for the Switch
  8. Open Source Contributions and Side Projects
  9. LinkedIn and Professional Networking
  10. Which Companies and GCCs Hire from IT Services
  11. Preparing for Product Company Technical Interviews
  12. Preparing for GCC Interviews
  13. Salary Expectations After Switching
  14. Realistic Timelines by Experience Level
  15. Common Mistakes That Kill the Switch
  16. Typical Transition Paths: What Actually Happens
  17. Frequently Asked Questions

Why Engineers Leave Infosys for Product Companies and GCCs

The reasons engineers leave IT services for product companies or GCCs cluster into four categories, and understanding which category drives your own motivation is important because each category points to a different type of target company.

The compensation gap. The salary differential between IT services companies and product companies or GCCs at equivalent experience levels is significant and well-documented. A Technology Analyst at Infosys with four years of experience earning 12 to 14 lakhs CTC is looking at a salary range of 18 to 35 lakhs for equivalent technical roles at mid-tier product companies and GCCs, and 35 to 80 lakhs at FAANG-tier companies. This gap is not a perception - it is a structural feature of how product companies monetise engineering talent differently from services companies. If compensation is the primary driver, GCCs typically offer the fastest salary improvement per unit of transition difficulty, while FAANG offers the highest ceiling but the steepest preparation requirement.

The technical stimulation gap. Engineers who are intellectually engaged by hard technical problems find that IT services delivery, particularly on maintenance and legacy modernisation accounts, does not provide the kind of engineering challenge that keeps them sharp. The frustration is specific: the work is not technically hard in the ways they value - it does not require designing scalable systems, thinking about algorithmic efficiency at scale, or building novel capabilities. It requires domain knowledge, project coordination, and careful execution of well-understood patterns. For engineers with strong technical foundations, this gap grows more frustrating over time, not less.

The ownership and impact gap. In IT services, the engineer builds for the client’s product, not Infosys’s product. The visibility of contribution is limited - a feature delivered to a client’s banking application is used by potentially millions of customers, but the engineer’s connection to those users is indirect and mediated through client feedback and CSAT scores. Product company engineers feel direct ownership of what they build. The gap between “I maintain someone else’s system” and “I am building something people use” is psychologically significant and drives a meaningful proportion of the services-to-product switch.

The career ceiling perception. Senior engineers at IT services companies sometimes look at the management-track, client-relationship-focused career path ahead of them and find it misaligned with their identity as technical practitioners. The perception - often accurate - that Infosys’s career ceiling for purely technical roles is lower than at product companies with dedicated individual contributor tracks (Staff Engineer, Principal Engineer, Distinguished Engineer) motivates the switch.

Understanding which of these motivates you helps avoid the mistake of targeting the wrong type of company. Someone driven primarily by technical challenge should not accept a GCC role in a business process automation team just because the salary is better - they will be solving the same category of problem in a different organisational context. Someone driven primarily by compensation can make the switch faster and with a lower preparation bar by targeting GCCs rather than FAANG.

Understanding the Product Company vs IT Services vs GCC Distinction

IT Services model. Infosys’s revenue is generated by delivering technology services to external clients. This means the product is the service, and the engineers are the delivery mechanism. The client owns the intellectual property, the product roadmap, the architecture decisions, and the user relationship. Infosys engineers work within parameters set by the client. The business model rewards scale, repeatability, and client satisfaction. The engineering culture reflects this: process discipline, documentation, communication, and reliable delivery are more central than algorithmic innovation.

Product company model. A product company’s revenue is generated by a product it owns and sells. Engineers at product companies are directly building the thing that generates revenue. The intellectual property is the company’s own. The scale, performance, and reliability of the product directly affects the company’s commercial success, which creates a direct engineering accountability that IT services does not have. Product companies need engineers who can design for scale, think about trade-offs independently, and own technical decisions end to end.

Global Capability Center (GCC) model. A GCC (also called a Captive Center or Centre of Excellence) is an offshore subsidiary of a multinational company that handles significant portions of that company’s technology, analytics, operations, or R&D work. GCCs in India are set up by banks, financial services firms, technology companies, e-commerce businesses, healthcare conglomerates, and manufacturing companies to access Indian engineering talent while maintaining direct control over the work and output. A Morgan Stanley Technology Centre in Bengaluru, a Goldman Sachs engineering centre in Hyderabad, or a Google GCC in Hyderabad employs software engineers who are directly employed by those global firms (not by an IT services intermediary).

GCCs offer a middle ground that many engineers underappreciate: they often pay significantly more than IT services companies, offer direct employment with the global brand, provide exposure to real product and technology problems rather than client delivery, and have a lower interview bar than pure product companies for many roles. The GCC at a bank is not building the same category of product as Google, but it is building real technology for a real business, and the engineering accountability is meaningfully higher than in an IT services context.

The interview difference. Product companies and GCCs interview very differently from IT services companies. Where Infosys’s selection process emphasises aptitude, foundational programming knowledge, and cultural fit, product companies and GCCs emphasise:

  • LeetCode-style algorithmic problem solving (medium to hard difficulty)
  • System design discussions for mid-career and senior roles
  • Behavioural interviews using the STAR (Situation, Task, Action, Result) methodology
  • Deep technical knowledge of specific domains (distributed systems, databases, networking, operating systems)

This interview format difference is the primary reason that engineers with three to five years of Infosys experience fail product company interviews. The interview is not measuring what Infosys work has trained them for.

The Skill Gap: What Infosys Builds and What It Does Not

Being honest about the skill gap is the prerequisite to closing it. The gap is real, it is specific, and it is closable - but not by pretending it does not exist.

What Infosys work does build. After three to five years at Infosys, a consistently-engaged engineer has: professional communication skills in a client-facing context (which product companies value), experience working in agile delivery teams with sprint cycles and code review culture, exposure to enterprise-scale codebases and the operational discipline required to maintain them safely, domain knowledge in the industries served (BFSI, retail, healthcare, manufacturing), working knowledge of cloud platforms (AWS, Azure, GCP) particularly for engineers in digital transformation practices, and professional conduct habits (documentation, meeting cadence, escalation awareness) that translate well to any engineering environment.

These are genuine skills. The mistake many engineers make is in thinking they are sufficient for a product company transition without the missing pieces.

What Infosys work typically does not build. The gaps that IT services work consistently fails to develop:

Algorithmic problem-solving at competitive depth. The coding done on typical Infosys projects - feature development, bug fixes, integration code, data transformations - does not require or reward the kind of algorithmic thinking that product company interviews test. An engineer who has written Java for four years at Infosys has developed implementation fluency, not algorithmic depth.

System design at scale. Designing a URL shortener that handles a billion requests per day, or a notification system for 100 million users, or a distributed cache layer that maintains consistency under network partitions - these are system design problems that product company engineers grapple with. Infosys engineers who have maintained existing systems or implemented defined features have not typically exercised the blank-page system design capability that mid-career product company interviews demand.

Data structures and algorithm implementation under time pressure. The practice of reading a novel algorithmic problem and implementing a correct, efficient solution in 45 minutes is a specific skill that Infosys work does not develop and that product company interviews heavily test.

Ownership of technical decision-making. In Infosys delivery, architectural decisions are either inherited from the existing client codebase or made by senior architects and technical leads. Junior and mid-level engineers operate within defined technical parameters. Product company interviews probe whether engineers can justify technical choices, understand trade-offs, and make decisions independently. This ownership capability is rarely developed in standard IT services roles.

Data Structures and Algorithms: The Non-Negotiable Gap

The coding interview at product companies and GCCs is non-negotiable. There is no path around it. Every target company in the product/GCC space conducts at least one coding round where the candidate solves algorithmic problems under time pressure, and the quality and correctness of those solutions is the primary signal the company uses to evaluate engineering capability.

Why product companies use algorithmic interviews. The algorithmic interview is not the perfect signal - it is a well-known and frequently criticised screening mechanism. But it is the dominant one because it is standardised, scalable, and relatively difficult to fake. A candidate who consistently solves medium-difficulty algorithmic problems correctly and efficiently has demonstrated a baseline of logical reasoning, implementation discipline, and problem-solving ability that correlates with engineering effectiveness even when the specific problems bear no resemblance to the job’s actual work.

The LeetCode preparation framework. The preparation framework that the community has converged on is LeetCode-based, and there are good reasons for this. LeetCode’s problem set covers the full range of topics tested in product company interviews and is calibrated to the difficulty levels used by different companies. The framework has three phases:

Phase 1 (Foundation): Solve all LeetCode Easy problems and LeetCode Medium problems in the following topics: Arrays, Strings, Two Pointers, Sliding Window, Hash Maps, Stacks, Queues, Basic Trees, Basic Graphs (BFS/DFS), and Sorting. This phase should yield approximately 100 to 150 solved problems and should be completed in two to three months with daily practice (minimum one to two problems per day).

Phase 2 (Core Patterns): Study and practice the following patterns in depth, using LeetCode Medium and Hard problems: Binary Search (on sorted arrays and on the answer), Backtracking, Dynamic Programming (1D and 2D), Tree traversal and manipulation (inorder, preorder, postorder, LCA), Graph algorithms (Dijkstra, topological sort, union-find), Heaps and Priority Queues, and Tries. This phase requires two to three months and should yield another 80 to 120 solved problems.

Phase 3 (Company-Specific): Solve problems tagged to the specific companies being targeted. LeetCode Premium provides company-tagged problem lists. Focus on the last 30 to 90 days of problems for companies that are actively recruiting. This phase runs concurrently with active applications and mock interviews.

The quality-over-quantity principle. Many engineers attempt to shortcut DSA preparation by solving as many problems as possible without deeply understanding each one. This produces a large problem count and a shallow skill. The correct approach is to study each problem until you can solve it without hints, understand the time and space complexity of the solution, understand why naive approaches fail, and articulate the key insight that makes the efficient solution work. Problems solved to this depth compound into genuine algorithmic understanding; problems solved by reading the answer and moving on do not.

Mock interviews. Solving problems alone in an untimed environment is not the same as solving them in the interview setting. Regular mock interviews - on platforms like Pramp, Interviewing.io, or with peer partners - build the interview execution skills that offline practice does not: thinking aloud, clarifying requirements, testing with examples, and communicating the approach while implementing it. Schedule at least one mock interview per week during the active application phase.

System Design: The Mid-Career Differentiator

System design interviews become relevant at approximately three to four years of experience and are the primary differentiator in interviews for mid-level and senior roles. For engineers targeting roles at the senior software engineer level (typically five to eight years of experience), system design performance is as important as coding performance.

What system design interviews test. A system design interview presents a vague, open-ended problem: “Design Twitter.” “Design a ride-sharing platform.” “Design a distributed cache.” The interviewer evaluates how the candidate breaks down a complex system into components, makes trade-off decisions, handles scale and reliability requirements, and communicates architectural choices clearly. The interview is not looking for a perfect architecture - it is evaluating the quality of the candidate’s engineering thinking.

The four pillars of system design. Effective preparation for system design interviews builds understanding across four pillars:

Scalability: How does the system handle ten times, one hundred times, or one thousand times the expected load? The answers involve horizontal scaling (adding more servers), vertical scaling (more powerful servers), caching (reducing database load), CDNs (distributing static content), and load balancing (distributing traffic). Understanding when each applies and why is the foundation.

Reliability and availability: How does the system behave when components fail? The tools include replication (copies of data in multiple locations), failover (automatic switching to backup systems), circuit breakers (preventing cascading failures), and idempotent operations (safely retrying failed requests). Understanding CAP theorem - the impossibility of simultaneously providing Consistency, Availability, and Partition tolerance in a distributed system - is essential for discussing trade-offs.

Storage: How is data stored, accessed, and organised? The choice between relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra, DynamoDB) depends on the data model, the access patterns, and the consistency requirements. Understanding when each is appropriate and what the specific trade-offs are is required for competent system design discussion.

Communication: How do components of the system communicate? REST APIs, message queues (Kafka, RabbitMQ, SQS), gRPC, and WebSockets each serve different communication patterns. Understanding the trade-offs (synchronous vs asynchronous, at-least-once vs exactly-once delivery, fan-out vs point-to-point) is essential for systems discussion.

The study approach for system design. Read “Designing Data-Intensive Applications” by Martin Kleppmann cover to cover - it is the most comprehensive single resource for the concepts underlying system design. Supplement with the system design primer on GitHub, which provides structured coverage of specific components. Study canonical system designs (URL shortener, news feed, rate limiter, distributed cache, search autocomplete) in depth, understanding not just the design but why each architectural decision was made. Then practice designing systems you have not studied, applying the principles to novel problems.

Connecting Infosys experience to system design. Engineers with Infosys experience often underestimate how much their project experience is relevant to system design discussions. An engineer who has worked on a cloud migration project understands infrastructure trade-offs. An engineer who has debugged production incidents on a high-traffic system understands operational reliability. An engineer who has optimised slow database queries understands storage and access patterns. The key is to explicitly connect this experience to system design vocabulary - to be able to say “on my Infosys project, we faced exactly this trade-off, and here is how we resolved it” in a way that demonstrates genuine understanding rather than just anecdote.

Domain and Technology Stack Depth

Beyond DSA and system design, product companies and GCCs evaluate technical depth in specific domains. The domain relevant to each role varies, but some areas are broadly valuable across many targets.

Cloud platform expertise. AWS, Azure, and GCP certifications and hands-on experience are valued across virtually every technology company hiring in India. The specific services that matter most: compute (EC2/VMs, Lambda/Functions), storage (S3/Blob, RDS, DynamoDB/Cosmos), networking (VPC, load balancers, CDN), and DevOps tooling (CodePipeline/Azure DevOps, CloudFormation/Terraform). Engineers who can discuss cloud architecture decisions - not just use individual services - are at a significant advantage.

Backend development depth. For backend engineering roles, depth in a specific backend stack (Java with Spring Boot, Python with FastAPI/Django, Node.js with Express, Go) is expected. “Depth” means understanding more than the framework’s basic usage: understanding how the framework handles concurrency, how to optimise database access patterns, how to structure large codebases for maintainability, and how to debug performance issues. This depth is developed through building real projects, not through reading documentation.

Database expertise. Understanding relational database internals (indexing strategies, query execution plans, transaction isolation levels, normalisation and denormalisation trade-offs) and working knowledge of at least one NoSQL database (MongoDB, Cassandra, or Redis) is expected for backend roles. An engineer who can explain why a specific query is slow and how to fix it demonstrates database depth that Infosys work sometimes develops but often does not.

Operating systems and networking fundamentals. Questions about OS internals (process vs thread, context switching, memory management, deadlock conditions) and networking (TCP/IP, HTTP/HTTPS, DNS, load balancing) appear in both system design discussions and direct technical questions at many product companies. These are areas where the CS degree curriculum provides the foundation but where Infosys work rarely reinforces it. Refreshing these fundamentals through a combination of reading (the “Systems Performance” book by Brendan Gregg for OS, and RFC documents for networking fundamentals) and building small projects that expose you to these layers is worthwhile.

Building Your Resume for the Switch

The resume for a product company application is fundamentally different from a resume for an IT services role or a lateral move within the IT services industry. The difference is not cosmetic - it is in what the resume communicates and how it is structured.

The impact-quantification principle. IT services resumes typically list responsibilities (“Responsible for developing backend APIs for the client’s order management system”). Product company resumes must list impact (“Built REST API layer serving 2 million daily requests with p99 latency under 100ms, reducing client-reported errors by 40 percent”). The transformation from responsibility to impact requires thinking about what actually changed because of the work: what volume it handled, what improvement it produced, what problem it solved, and what the measurable outcome was.

For engineers who have worked on IT services projects where the “volume” and “metrics” were not part of daily vocabulary, this requires some retrospective work. Talk to your manager, look at monitoring dashboards, ask the client-side counterpart what metrics they track. Most projects have measurable outcomes that are not routinely documented but are discoverable with effort. Find three to five specific, quantified impact statements from your Infosys experience.

Technology stack translation. An Infosys resume that lists “Java, Spring Boot, Oracle, Git, JIRA” is technically accurate but misses the opportunity to signal depth. A product company resume should be specific about what was done with the technology: “Built microservices with Spring Boot using event-driven architecture on Kafka, handling 500K daily events with less than 200ms processing latency.” The specificity signals that the experience was not passive exposure but active, deep engagement.

Restructuring the project section. The projects section on an IT services resume often lists multiple large, multi-year client projects with a brief responsibility description. For a product company transition, reduce this to the two or three projects that produced the most technically interesting or impactful work, and describe each in the impact-quantified format. Add a side projects section immediately after the professional experience section, since product companies weight personal projects heavily as evidence of technical initiative beyond the day job.

The summary statement. Many IT services resumes begin with a summary statement that reads like a job description (“Results-driven software engineer with X years of experience in Java and Spring Boot looking for opportunities in technology”). Product company resumes should have a summary that is specific and positioned: “Backend engineer with four years of experience building high-throughput Java microservices for enterprise financial systems, currently expanding into distributed systems design and competitive algorithmic problem-solving for product company transition.” This summary signals awareness of the gap and active effort to close it, which is more credible than pretending the gap does not exist.

One page vs multiple pages. For candidates with fewer than eight years of experience, a two-page maximum is strongly preferred by product companies and GCCs. The constraint forces prioritisation - only the most relevant and impactful experience makes it in. A three-page IT services resume padded with client project lists, certification lists, and training course completion lists signals a services-company mentality, not a product-company one.

ATS optimisation. Most large companies and GCCs use Applicant Tracking Systems that scan resumes for keyword matches before human review. Include the technology keywords from the job description in the resume (AWS, Kubernetes, React, Python, distributed systems, REST APIs - whatever the role specifies). Use the exact phrasing from the job description where the skills genuinely apply. A resume that does not pass ATS screening never reaches a human reviewer regardless of quality.

Open Source Contributions and Side Projects

Open source contributions and side projects are the most visible evidence that a services-company engineer has initiative and capability beyond the job requirement. They are disproportionately weighted by product company hiring managers because they answer the implicit question: “Does this person code when no one is requiring them to?”

Why this matters for the transition. An engineer with three years at Infosys and a GitHub profile showing active contributions to open source projects, or a portfolio of personal projects with real functionality and quality code, is immediately more credible as a product company candidate than an identical engineer with an empty GitHub profile. The signal is not about the specific projects - it is about the demonstrated intrinsic motivation to build.

How to start contributing to open source. Start with issues labelled “good first issue” or “beginner friendly” on GitHub. These are explicitly designed for new contributors and provide an onboarding path into a codebase. Good starting points include: popular open source projects in the technology stack you are targeting (a Java backend developer contributing to a Java framework, a Python developer contributing to a popular Python library), documentation improvements (which are valuable contributions with a lower barrier to entry), and bug fixes for clearly described issues.

The goal is not to become a core maintainer overnight. Even a few merged pull requests demonstrate the ability to read unfamiliar code, understand contribution standards, and work within an open source governance model. This is genuinely valuable experience and is a credible talking point in product company interviews.

Side project strategy. Side projects for transition purposes should be built to demonstrate the specific skills that product companies value, not just to produce something functional. The most impactful side projects:

Build something that requires handling scale, even if simulated: a REST API with caching, rate limiting, and monitoring; a data pipeline that processes large volumes; a real-time application using websockets.

Use the technology stack of the target role: if you are applying for cloud-focused roles, build something deployed on AWS with infrastructure as code. If you are applying for React/Node roles, build a full-stack application with real functionality.

Are visible and documented: host the code on GitHub, write a clear README that explains the problem solved, the architecture decisions made, and the trade-offs considered. Deploy the project and link to the live version. Write a short blog post about what you built and what you learned.

The 20 percent time approach. The practical constraint for most engineers attempting this transition while employed full-time at Infosys is time. The most sustainable approach is treating skill development and side project work as a dedicated 20 percent time investment - approximately eight to ten hours per week - rather than trying to do everything at maximum intensity and burning out in four weeks. A consistent eight hours per week compounds into over 400 hours of preparation over a year, which is sufficient for a meaningful transition if allocated to the right activities.

LinkedIn and Professional Networking

LinkedIn is the most important single platform for the IT-services-to-product-company transition, and most IT services engineers significantly underutilise it.

The recruiter pipeline. Product companies and GCCs have internal talent acquisition teams and external recruiters who actively source candidates on LinkedIn. Engineers who have never received a LinkedIn message from a Google, Amazon, or GCC recruiter are almost certainly not appearing in the searches these recruiters run. The searches use specific criteria: skills tags, current company, title, and sometimes specific text in the profile. Optimising the LinkedIn profile to appear in these searches is a passive but effective channel for inbound opportunities.

Profile optimisation for product company targeting. The LinkedIn profile should mirror the resume in its impact-quantified experience descriptions, but it has additional tools: the skills endorsements section (add every relevant technology skill and ask colleagues to endorse the most important ones), the featured section (pin the GitHub profile, any published articles, any project demos, or any relevant recognition), and the about section (which can be written in a more personal voice than the resume summary and should explicitly communicate the product company transition aspiration).

The headline as a signal. The default LinkedIn headline shows the current job title at the current company. A custom headline that signals the transition direction - “Backend Engineer Java, Spring Boot, AWS System Design Transitioning to Product Engineering” - appears in recruiter searches and immediately communicates the target to anyone who views the profile. This specificity is more effective than a generic title.

Connecting with target company engineers. Sending personalised connection requests to engineers at target companies is one of the most direct networking activities available. The request message should be specific and brief: mention the shared background (both worked in Java backend, both are from Bengaluru, both went through a similar transition), acknowledge the specific company, and ask a concrete, answerable question. Most people do not respond, but a 10 to 15 percent response rate on thoughtful outreach is achievable, and a single conversation with a current Google or Amazon employee provides transition insight that no guide can fully replicate.

LinkedIn’s “Open to Work” feature. The Open to Work setting on LinkedIn can be configured to be visible only to recruiters, not to the public network. For engineers who do not want their current Infosys management to know they are exploring options, this private setting allows inbound recruiter outreach without a public signal. Activate this and be specific about the types of roles and locations you are targeting - recruiters use these filters.

Publishing on LinkedIn. Engineers who write and publish posts about technical topics they are learning - system design concepts, DSA problem walkthroughs, comparisons of technology approaches - build a professional presence that passive profile maintenance does not. This is not about virality; it is about demonstrating genuine technical engagement to the recruiters and hiring managers who will view the profile during candidate review. Five well-written technical posts over three months is more impactful than 50 forwarded news articles.

Which Companies and GCCs Hire from IT Services

The target company landscape for IT services-to-product transition candidates is larger and more varied than most engineers realise. Understanding the landscape prevents the common mistake of narrowing preparation to FAANG and missing the broad middle tier of excellent opportunities.

FAANG and FAANG-adjacent. Google, Amazon, Meta, Microsoft, Apple, and Uber/Lyft/Airbnb represent the highest compensation and highest interview bar tier. These companies hire from IT services backgrounds when the candidate has done the work to close the skill gap - typically 12 to 24 months of serious DSA and system design preparation. The bar is not insurmountable for IT services engineers; it is simply not achievable without sustained, deliberate preparation that goes well beyond what IT services work develops.

Amazon is the most accessible of this tier for IT services engineers because of its volume of hiring, its India presence (Amazon India, AWS India), and its systematic interview process that is somewhat more learnable than Google’s. Microsoft’s Indian GCC (Microsoft India Development Centre in Hyderabad) hires a significant volume of engineers from IT services backgrounds for mid-level roles. Google hires IT services engineers but the bar is higher and the volume is smaller.

Product companies at the mid tier. Companies like Atlassian, Intuit, LinkedIn (Microsoft), Salesforce, Adobe, and Zoho hire significant volumes from IT services backgrounds and have interview processes that are rigorous but more attainable with eight to twelve months of focused preparation. These companies offer excellent compensation (typically 25 to 60 lakhs for mid-level roles in India), strong technical environments, and product ownership that IT services does not provide.

Indian product companies. Flipkart, Swiggy, Zomato, Razorpay, Freshworks, BrowserStack, PhonePe, and Meesho are Indian product companies with strong engineering cultures that actively hire from IT services. These companies are particularly relevant for engineers who want product company experience without relocating or dealing with the complexity of GCC hiring processes. Compensation at top Indian product companies is competitive with many GCCs and significantly above IT services.

Global Capability Centers in India. GCCs represent perhaps the largest opportunity for IT services engineers making the transition. The major GCCs in India hiring from IT services include:

Financial services GCCs: Goldman Sachs Technology Centre (Bengaluru, Hyderabad), Morgan Stanley India, JPMorgan Chase India, Citibank Technology India, HSBC Technology India. These hire at significantly higher salaries than IT services (typically 20 to 45 lakhs at mid level) and work on real financial technology systems. The interview process includes DSA (typically medium difficulty), system design basics, and domain knowledge relevant to the financial services context.

Technology company GCCs: Google India, Amazon India (AWS), Microsoft IDC, SAP Labs India, Oracle India, IBM India. These have interview processes close to their parent company standards and compensation to match.

E-commerce and consumer GCCs: Walmart Global Tech, Target Tech, Lowe’s Technology Centre India, and similar retail technology GCCs offer strong engineering environments focused on high-scale consumer systems.

Automotive and manufacturing GCCs: Continental, Bosch, Honeywell, Caterpillar, and similar companies have engineering-focused GCCs for embedded systems, automotive software, and industrial IoT - relevant for engineers from electronics or mechanical engineering backgrounds.

Factors that determine target company fit. When choosing which companies to target, consider: the technology stack alignment (does the target company use the technology you are building depth in?), the interview process difficulty (is your current preparation level realistically sufficient, or would you need additional months?), the industry domain (do you have relevant domain knowledge from Infosys project experience that makes you more competitive?), and the compensation expectations (are they achievable within the role tier you qualify for?).

Preparing for Product Company Technical Interviews

The technical interview preparation for a product company application has three distinct components, each requiring dedicated preparation.

The phone screen. The initial technical screen is typically a 45 to 60 minute call with a recruiter or engineer. It usually includes two medium-difficulty LeetCode problems, sometimes one easy and one medium, and occasionally a discussion of a past project or system. The phone screen filters the candidate pool significantly - most candidates who fail at the phone screen fail on the coding component, not on the discussion.

Preparation specifically for phone screens: practice solving problems while explaining your thinking aloud (since the interviewer is listening and evaluating your communication, not watching your screen). Use a plain text coding interface (not an IDE) and practice typing code without auto-complete. Time yourself: 20 to 25 minutes per problem is the target. Practice starting with clarifying questions (edge cases, input constraints, expected output format) before writing any code.

The onsite or virtual onsite loop. The full interview loop typically consists of three to six rounds covering: two to three coding rounds, one system design round (for mid-level and senior candidates), one behavioral round, and sometimes a domain-specific technical discussion. The rounds are usually conducted the same day (virtual onsite) or over consecutive days (for in-person formats that some companies use).

For coding rounds: the problems are medium to hard difficulty, and the expectation is not just a correct solution but clean, efficient code that the candidate can discuss, test, and optimise. Practice writing code in an interviewing environment (CoderPad or similar) with another person watching. The pressure of being observed degrades performance significantly for engineers who have only practised alone.

For the system design round: use a structured framework that consistently covers: clarifying requirements (functional and non-functional), estimating scale (users, requests, data volume), identifying components (API layer, database, cache, message queue), drawing the architecture, discussing trade-offs, and diving deep on one or two components. Practice this framework on five to ten system design problems before the interview, ideally with a peer who can ask probing questions.

The behavioral round. Product companies and GCCs conduct behavioral interviews using the STAR methodology (Situation, Task, Action, Result). The questions probe for specific examples of past behaviour in situations relevant to the role: “Tell me about a time you disagreed with your team about a technical decision and how you handled it.” “Describe a situation where you had to deliver under significant time pressure.” “Give me an example of when you had to learn a new technology quickly.”

Prepare five to seven STAR stories from Infosys experience that cover: a technical challenge overcome, a conflict or disagreement navigated, a time you showed leadership without formal authority, a time you failed and what you learned, and a time you delivered despite ambiguity or incomplete information. Each story should be two to three minutes when told aloud. The behavioral round is frequently under-prepared by engineers who focus exclusively on the technical preparation, and consistently strong behavioral performance is a differentiator.

Amazon’s leadership principles. Amazon’s behavioral interview is specifically structured around its 14 leadership principles (Customer Obsession, Ownership, Invent and Simplify, Are Right A Lot, Learn and Be Curious, Hire and Develop the Best, Insist on the Highest Standards, Think Big, Bias for Action, Frugality, Earn Trust, Dive Deep, Have Backbone, Deliver Results). Study these principles and prepare at least one STAR story that demonstrates each of the most relevant ones. Amazon interviewers explicitly ask for leadership principle demonstrations, and candidates who have not prepared accordingly are visibly underprepared.

Translating IT services experience into behavioral stories. The behavioral interview is where Infosys experience is genuinely transferable - if correctly translated. Stories about managing client escalations demonstrate Earn Trust and Customer Obsession. Stories about pushing back on technically unsound decisions in a team setting demonstrate Have Backbone. Stories about learning a new technology stack under project pressure demonstrate Learn and Be Curious. The raw material from Infosys projects is there; the skill is in structuring it using STAR and in connecting it explicitly to the leadership principle being probed.

The mistake IT services engineers make in behavioral interviews is describing collective team outcomes (“we delivered the project on time”) rather than individual actions and individual impact (“I identified that the database indexing strategy was causing the latency spike, proposed the fix to the technical lead, implemented it in a two-day sprint with a measurable 60 percent latency reduction, and documented the approach in the runbook”). The individual-action framing is what the behavioral interviewer is evaluating - not whether the team succeeded, but what this specific person did.

Practicing behavioral answers aloud. Writing STAR stories in a document is useful for structuring the content, but the delivery matters enormously. Recording yourself giving the answers - on video or audio - and reviewing the recording is uncomfortable but extremely revealing. Most engineers discover they are significantly more verbose than they need to be (two-minute answers that could be 90 seconds with better editing), that they unconsciously use filler words or pause awkwardly, or that the narrative loses focus midway. Refining the answer after reviewing the recording produces a meaningfully more polished interview performance.

The Interview Loop Mechanics: What to Expect Round by Round

Understanding the mechanical structure of a product company interview loop prevents the surprise and disorientation that candidates who have only experienced Infosys-style hiring feel during their first product company loop.

Resume screening and recruiter outreach. The first step is either applying online and waiting for a recruiter screen, or being contacted directly by a recruiter through LinkedIn. The recruiter screen is typically 30 minutes, covers the resume at a high level, discusses the role and compensation expectations, and assesses basic communication and role alignment. This round rarely filters out candidates on technical grounds unless the experience is clearly misaligned. Be direct about compensation expectations and about the specific role targets.

The online assessment. Many companies send an online coding assessment (via HackerRank, CodeSignal, or similar) after the recruiter screen. This is typically two to three problems solved in 60 to 90 minutes. The problems are usually Medium difficulty. Performance on this assessment determines whether the candidate advances to the full loop. Treat this as seriously as the onsite interview - many candidates who prepare for the onsite but not the online assessment are filtered out here.

The phone screen. If the OA passes, a phone screen (or video screen) with an engineer follows. This involves one to two coding problems and sometimes a brief discussion of past projects. The interviewer is typically a software engineer, not a recruiter. This round has a higher bar than the OA and is where many under-prepared candidates are eliminated.

The onsite or full loop. The full interview loop is the most intensive phase. At Google it is typically four to five rounds over one day. At Amazon it is typically four to five rounds over two days with a “bar raiser” panel. At mid-tier companies it is typically three to four rounds. Each round serves a specific purpose: coding, system design, behavioral, and sometimes a manager or cross-functional discussion.

The debrief and offer process. After the loop, the hiring committee reviews all interview feedback and makes a hire/no-hire recommendation. At Google this process can take one to three weeks. At Amazon it is typically faster (one to two weeks). At smaller companies it can be within days. The offer comes through the recruiter and is negotiable. The gap between the initial offer and the final offer after negotiation is typically 10 to 20 percent total compensation for candidates who negotiate effectively.

Managing multiple loops simultaneously. The correct strategy during active applications is to have three to five companies in the pipeline simultaneously, at different stages of the process. This creates competitive tension (which improves offer negotiations), provides a fallback if one company’s loop does not proceed, and gives experience with the interview format across multiple companies even if not all loops result in offers. Coordinating timing - trying to have multiple offers arrive close together - gives maximum negotiating leverage and is worth explicitly communicating to recruiters: “I have another process that is moving toward an offer stage; is there any flexibility in your timeline?”

The Mental and Emotional Dimension of the Transition

The transition from IT services to a product company is not only a technical and tactical challenge. It has a significant psychological dimension that most guides do not address but that affects outcomes substantially.

Imposter syndrome in the preparation phase. Engineers who begin solving LeetCode problems for the first time after three to four years of Infosys work frequently experience intense imposter syndrome. The problems feel harder than expected. The solutions that seem obvious in editorial explanations are not obvious in practice. The Codeforces rating does not move for weeks. The inner voice saying “I am not cut out for product company work” is common and is almost always wrong - it reflects the gap between the skill required and the current skill, which is exactly what preparation is designed to close.

The productive response to imposter syndrome during preparation is not to dismiss it but to reframe it: “The discomfort I am feeling is evidence that I am working at the edge of my capability, which is exactly where growth happens.” Set small, daily goals that are achievable and visible - solving one LeetCode medium problem per day, for example - and track progress in a log. The accumulated evidence of daily progress is the most reliable antidote to the imposter syndrome narrative.

Handling failed interview rounds. Failed interview rounds are a normal part of the transition process. Most successful transitioners have failed at least two to three interview loops before receiving an offer. The correct response to a failed round is: request feedback from the recruiter (rarely provided but occasionally useful), independently analyse what went wrong (was it a specific algorithmic technique you did not know? A system design component you had not studied? A behavioral question you were not prepared for?), address the specific gap, and set a schedule for the next application wave.

The mistake is treating a failed interview as evidence that the switch is impossible, rather than as data about a specific gap in preparation. Keep a log of failed interview rounds and the specific points where the round went wrong - this log is the most honest source of preparation feedback available.

Talking to people who have made the switch. One of the most effective psychological interventions for engineers attempting this transition is having regular conversations with engineers who have successfully made it. Former Infosys colleagues who have switched, LinkedIn connections at target companies who are willing to have coffee chats, and communities of IT-services-to-product-company transitioners online all provide the normalising evidence that the switch is made by real people with real backgrounds, not by exceptional people with exceptional circumstances.

The “enough preparation” threshold. A common failure mode is never feeling ready to apply. Engineers spend 18 months in preparation, pass mock interviews consistently at the Medium level, but keep extending the preparation because they feel the Hard problems are not solid enough or the system design is not polished enough. This extended preparation without applying is its own failure mode. The rule should be: when you are consistently solving Medium problems on the first attempt within 30 minutes and can pass a structured system design mock without major gaps, begin applying. Refinement happens through actual interview feedback, not through indefinite additional preparation.

The calendar commitment. The engineers who successfully complete the transition are almost uniformly those who made preparation a scheduled, non-negotiable calendar commitment rather than a “when I have energy” activity. Two hours from 6 to 8 AM before work, or 9 to 11 PM after the family has settled, every weekday - this is more sustainable and more productive than sporadic intense sessions. Treat the preparation schedule with the same respect given to work meetings.

Common Mistakes That Kill the Switch

The resume and LinkedIn profile tell product companies and GCCs what you claim to have done. The portfolio - the GitHub repositories, deployed projects, blog posts, and open source contributions - shows what you have actually built. For IT services engineers, the portfolio is often the weakest component and the one with the most leverage.

GitHub as your technical identity. A product company recruiter or engineering manager who looks at a candidate’s GitHub profile and sees consistent activity (commits across multiple projects over a sustained period), readable and well-documented code, evidence of learning (progression from simpler to more complex projects), and engagement with the broader software community (stars on other projects, follow of relevant engineers) receives a signal that an empty GitHub profile simply cannot provide.

Maintaining GitHub activity does not require constant heroic effort. Three to four commits per week on a real project - even a simple one you are building for learning purposes - keeps the activity graph green and signals consistent engagement. The most common mistake is building a project in a weekend burst, abandoning it, and never returning. Projects that are started and abandoned visible on GitHub can actually be a negative signal.

What makes a side project strong. A strong side project for the product company transition context has all of these: a clearly defined problem it solves (stated in the README), non-trivial technical implementation (not a tutorial clone), evidence of engineering decisions documented (the README should explain why certain architectural choices were made), a deployed and accessible version (even a Heroku or Railway free tier deployment), and clean, readable code that is covered by at least basic tests. A project that meets these criteria is a talking point in the interview and evidence of engineering maturity.

Blog posts as technical demonstration. Writing technical blog posts - on Medium, Hashnode, personal blog, or even LinkedIn articles - serves two purposes: it demonstrates communication capability (a highly valued product company skill), and it demonstrates the depth of understanding needed to explain a concept clearly to an audience. Topics worth writing about for transition purposes: deep dives into a technology used in a side project, comparisons of architectural approaches for a specific problem, walkthroughs of how you solved a specific LeetCode problem pattern or system design challenge, and lessons learned from Infosys project experience that are relevant to product engineering contexts.

The publication of technical content, even if not widely read, demonstrates initiative and communication quality in a way that a resume bullet point never can.

GCC interview preparation overlaps significantly with product company preparation but has some specific differences that are worth understanding.

Domain knowledge is more valued. GCCs, particularly financial services GCCs, weight domain knowledge alongside pure algorithmic skill. An engineer who has worked on a banking or insurance project at Infosys and has developed genuine understanding of financial concepts (reconciliation, settlement, regulatory reporting, payment processing) has a genuine advantage in Goldman Sachs or JPMorgan GCC interviews over an engineer with equal DSA skill but no domain background.

The algorithmic bar varies. FAANG GCCs (Google India, Amazon India) interview at essentially FAANG standards. Financial services GCCs typically interview at a medium-difficulty algorithmic level without the hard LeetCode problems that FAANG uses. Retail and consumer goods GCCs vary widely. Research the specific company’s interview pattern through Glassdoor and LinkedIn connections before calibrating the preparation intensity.

Cultural fit with the parent company. GCCs are extensions of their parent companies and carry the parent’s culture into the interview process. An Amazon GCC interview feels like an Amazon interview - the same leadership principles, the same technical bar, the same behavioral framework. A Goldman Sachs GCC interview reflects Goldman’s culture: direct, quantitative, comfortable with ambiguity in financial contexts, and focused on the candidate’s ability to handle complexity. Understanding the parent company’s culture and signalling cultural alignment is as important as technical performance in GCC interviews.

The compensation negotiation. GCC offers are often initially lower than what the market bears for the role, particularly for candidates coming from IT services where the current CTC is used as the baseline. Having a clear external market benchmark (from LinkedIn salary data, Glassdoor, or peer conversations) and being willing to negotiate with specific data is important. GCCs have salary flexibility but may not use it without explicit negotiation. Never accept the first number without at least one counter.

Salary Expectations After Switching

The salary improvement from switching to a product company or GCC is real and significant. Understanding the realistic ranges prevents both under-negotiating and holding out for unrealistic numbers.

From Infosys to GCC (financial services). A Technology Analyst at Infosys earning 12 to 14 lakhs CTC with four years of experience can realistically expect 22 to 38 lakhs at a financial services GCC (Goldman Sachs, JPMorgan, Morgan Stanley India, Barclays, Deutsche Bank GCC) for an equivalent backend engineering role. The exact number depends on the interview performance, the specific company’s India compensation benchmarks, and the candidate’s specialisation.

From Infosys to mid-tier product companies. Engineers switching to mid-tier product companies (Atlassian, Intuit, Freshworks, Razorpay, Swiggy, Zomato) with four to six years of experience and solid DSA/system design preparation can expect 25 to 50 lakhs depending on the level at which they are hired and the performance in the interview loop.

From Infosys to FAANG. The compensation at FAANG companies for mid-level engineers (L4/L5 at Google, SDE2 at Amazon, etc.) in India is 50 to 1 crore+ depending on the exact level, the RSU grant, and the annual performance bonus. These numbers are the top of the range and require interview performance at the top of the candidate distribution, not just passing the bar.

The non-salary compensation picture. Equity compensation (RSUs, ESOPs, stock options) is a significant component at product companies that does not exist at Infosys. An Amazon SDE2 offer at 60 lakhs total CTC may include 15 to 20 lakhs in annual RSU grants that vest over four years. Understanding the vesting schedule, the current stock value, and the performance conditions on equity is essential for evaluating offers that include equity components.

The negotiation approach. When negotiating a product company or GCC offer: research the market compensation for the specific role level at the specific company through LinkedIn salary data, Glassdoor, levels.fyi, and peer conversations. Have at least one competing offer or a credible alternative, and be willing to mention it. Counter-offering with a specific number and a specific justification (“My research shows the market rate for this role level at peer companies is X, and I have a competing offer at Y”) is more effective than a vague request for more. Most offers have 10 to 20 percent flexibility in total compensation for candidates who negotiate professionally.

Realistic Timelines by Experience Level

The preparation timeline for a successful transition depends heavily on the starting experience level, the target company tier, and the intensity of preparation investment.

One to two years of Infosys experience. Engineers at this stage are close enough to their academic preparation that the DSA gap is smaller than for more senior engineers, but they lack the project experience and system design exposure that mid-level roles require. The realistic target is: GCCs at associate engineer level, Indian product companies (Zomato, Swiggy, Freshworks, CRED), and mid-tier technology companies. Timeline with focused preparation: eight to twelve months of DSA preparation (targeting a LeetCode rating in the Medium comfortable zone) and an initial system design overview without deep knowledge. The compensation improvement at this level may be modest - from 6 to 8 lakhs at Infosys to 12 to 22 lakhs at a target company.

Two to four years of Infosys experience. This is the most common transition window and the one with the highest success rate when preparation is done correctly. Engineers have enough project experience to have relevant talking points for behavioral and project-based interviews but are not so senior that the system design expectation is overwhelming. Timeline with focused preparation: ten to fourteen months for a mid-tier product company target, twelve to eighteen months for FAANG-tier targets. The compensation improvement at this level is significant: from 12 to 18 lakhs at Infosys to 25 to 60 lakhs at product companies.

Four to six years of Infosys experience. Engineers at this level are at the Technology Analyst to Senior Technology Analyst band and have strong project experience and domain knowledge. The gap in DSA is significant after several years without algorithmic practice. System design becomes a more important component of the interview loop. Timeline with focused preparation: twelve to twenty months for mid-tier product company targets, sixteen to twenty-four months for FAANG-tier. The compensation improvement can be transformative: from 16 to 25 lakhs at Infosys to 40 to 100 lakhs at product companies.

Six or more years of Infosys experience. At this level, engineers bring substantial domain expertise, delivery leadership experience, and deep technical knowledge in specific areas. The DSA gap may require more focused remediation but the system design and behavioral components are stronger. The target roles at this experience level are senior engineer, lead engineer, or engineering manager positions at product companies and GCCs. Timeline: twelve to eighteen months of focused preparation, potentially longer for the most senior FAANG-tier targets. The compensation improvement from Technology Lead at Infosys (25 to 35 lakhs) to a senior product company role (60 to 150 lakhs) can be two to four times.

Common Mistakes That Kill the Switch

Applying before the preparation is ready. The most damaging mistake is applying to target companies before the DSA and system design preparation reaches the required level. Failed interviews at target companies leave a cooling period before reapplication (often six months to a year) and waste opportunities. The correct sequence is: build the skills first, apply when the mock interview performance consistently clears the target bar.

Targeting only FAANG. Engineers who focus exclusively on Google, Amazon, Meta, and similar top-tier companies often spend 18 months in preparation, fail three rounds at one company, and become discouraged. Meanwhile, ten to fifteen mid-tier product companies and GCCs with excellent compensation would have been attainable with eight months of preparation. Diversify the target list across tiers.

Resume that reads like an IT services profile. The services-company resume structure (client list, technology tool list, project responsibilities list) is immediately identifiable to product company hiring managers and signals a services-company mindset. The resume must be rewritten, not reformatted, for the product company context.

Neglecting the behavioral interview. Engineers who invest all their preparation time in DSA and system design and zero time in behavioral interview preparation are caught flat-footed by questions they have not prepared for. Amazon in particular eliminates candidates at the behavioral round who cannot provide specific, structured STAR examples. Behavioral preparation should be allocated at least 10 to 15 percent of total interview preparation time.

Not leveraging the IT services network. Engineers who left IT services for product companies are now working at those companies. Peers from Infosys who have made the switch are the most accessible and candid source of specific information about the target company’s interview process, culture, and realistic compensation. Most people are willing to share their experience and to provide referrals to former colleagues. Not using this network is leaving the most valuable resource on the table.

Switching only for salary. Engineers who switch purely for compensation and take any offer that pays more than Infosys often find themselves in a GCC or mid-tier company role that is as intellectually unchallenging as their IT services work, at a higher salary but with no improvement in the career dimensions that actually matter. Evaluate the role, the team, and the engineering culture alongside the compensation.

Giving up after the first failure. The first product company interview loop that a typical IT services engineer attempts will fail. The preparation is rarely sufficient after the first wave of applications. The correct response is to review what went wrong (request feedback where possible, identify the specific technical gaps exposed), address those gaps, and attempt again in three to six months. Most successful transitions involve at least two waves of applications.

Underestimating the behavioral round. Engineers who invest all preparation time in DSA and system design and zero time in behavioral interview preparation are caught flat-footed by questions they have not prepared for. Amazon in particular eliminates candidates at the behavioral round who cannot provide specific, structured STAR examples. Behavioral preparation should be allocated at least 10 to 15 percent of total interview preparation time.

Treating mock interviews as optional. Solving LeetCode problems alone is fundamentally different from solving them in an interview setting with another person watching and evaluating. The cognitive load of thinking aloud, managing time visibly, clarifying requirements under mild social pressure, and communicating the approach while implementing it is different enough that candidates who have only practised alone systematically underperform their preparation level in actual interviews. Mock interviews on Pramp, Interviewing.io, or with a prepared peer are not a nice-to-have - they are how the interview execution skill is built.

Not researching the company before each interview. Product company interviews almost always include a round where the candidate is asked why they are interested in the specific company. A vague answer (“It is a great company with excellent growth opportunities”) is an immediate signal of low engagement. Research the company’s technology blog, understand their primary products and engineering challenges, read about their engineering culture, and form a genuine opinion about what specifically attracts you. “I have been following your work on distributed transactions in your payments infrastructure and I want to work on problems at that scale” is a compelling answer. Generic enthusiasm is not.

Applying to a single company at a time. The product company hiring process is slow (four to eight weeks per loop typically) and unpredictable (offers fall through, roles get closed, hiring freezes happen). Engineers who apply to one company at a time and wait for the outcome before applying to the next will spend 12 to 18 months in the application phase when they could complete the same number of loops in six to eight months by running three to five processes simultaneously. The pipeline approach is more efficient and provides the competitive leverage needed for salary negotiation.

Typical Transition Paths: What Actually Happens

These are the patterns that characterise successful transitions from Infosys to product companies and GCCs, drawn from the trajectories of engineers who have made the switch.

The stepping stone path. This is the most common successful trajectory. The engineer spends one to two years at Infosys, invests eight to twelve months in preparation (DSA, system design, resume rebuilding), and makes a first move to a mid-tier product company or GCC (say, a financial services GCC at 25 to 35 lakhs or an Indian product company at 20 to 30 lakhs). After two to three years at the mid-tier company building genuine product engineering experience, the engineer attempts FAANG-tier companies and succeeds because they now have product company experience on their resume in addition to strong preparation. This two-hop transition is more reliable than a direct Infosys-to-FAANG attempt for most engineers.

The Indian product company path. Engineers who join strong Indian product companies (Flipkart, Swiggy, Razorpay, PhonePe, CRED) from Infosys build genuine product engineering credentials in two to three years. The technical environment at these companies is strong, the scale challenges are real (India’s internet economy is large), and the compensation is competitive. After three to four years at a top Indian product company, the resume is product-engineering-credentialed and the FAANG interview success rate is much higher.

The GCC-to-product path. Engineers who move to a financial services GCC or a technology company GCC from Infosys often find the GCC provides both the compensation improvement they need and the technical environment that builds the missing skills (distributed systems, high-scale infrastructure, rigorous engineering process). After two to three years at the GCC, with continued DSA practice and system design exposure from the GCC’s work, the path to a product company becomes more direct.

The direct FAANG path. Some engineers succeed at making the direct transition from Infosys to FAANG, but the profile is specific: the engineer was already strong in competitive programming from college (InfyTQ DSE or HackWithInfy finalist background), invested 18 to 24 months of serious preparation, has a GitHub portfolio and at least one meaningful open source contribution, and passed the mock interview bar consistently before applying. This path is available but is not the representative case for most IT services engineers.

The preparation journey more than the destination. Engineers who spend two years seriously preparing for a product company transition - even those who end up at a GCC or mid-tier product company rather than FAANG - are universally better engineers at the end of that period than they were at the beginning. The DSA practice sharpens algorithmic thinking. The system design study deepens architectural intuition. The behavioral preparation increases self-awareness and communication clarity. The preparation journey has intrinsic career value independent of the specific landing place.

What the transition looks like from the inside. The lived experience of engineers making this transition - as reported by those who have completed it - follows a consistent arc: the first three to four months of LeetCode practice feel like fighting a headwind, with many problems taking far longer than expected and frequent frustration at the gap between where the preparation is and where it needs to be. Months four through eight typically show a visible shift as the patterns begin to connect - the recognition of a sliding window problem, a binary search on the answer, or a classic BFS structure happens faster, and the implementation becomes more fluent. The final phase, months eight through twelve or beyond, involves mock interviews that increasingly feel manageable rather than terrifying. The first successful technical phone screen with a product company is often described as genuinely transformative - a tangible confirmation that the preparation has produced a real capability change, not just a credential.

This arc is worth knowing in advance because the first three to four months are where most preparation attempts collapse. The difficulty is real and is not a sign that the switch is impossible - it is a sign that the preparation is working at the edge of the current capability, which is exactly where skill development happens.

Frequently Asked Questions

1. Is it really possible to switch from Infosys to Google or Amazon?

Yes, it is genuinely possible and it happens every hiring cycle. The candidates who succeed typically have invested 12 to 24 months of serious preparation in DSA (consistently solving Medium problems, some Hard problems), system design (studied from “Designing Data-Intensive Applications” and practiced canonical designs), and behavioral interview preparation (STAR stories prepared for each major competency). The transition is not easy, but it is not closed to IT services engineers. Most successful transitioners have two to four years of Infosys experience when they make the move, have done significant side project work, and have at least one strong competitive signal (LeetCode rating, HackWithInfy performance, or open source contributions).

2. How long does the preparation take?

The honest answer is 10 to 18 months of serious preparation for mid-tier product company and GCC targets, and 15 to 24 months for FAANG-tier targets, for engineers starting from a typical IT services background without prior competitive programming or algorithmic practice. Engineers who were strong competitive programmers in college and have maintained that skill can be ready faster. Engineers who are starting DSA for the first time while working full-time should plan for the longer end of these ranges.

3. Should I quit Infosys first or prepare while employed?

Prepare while employed unless the situation is financially unsustainable or professionally harmful. Quitting before securing a new offer creates financial pressure that degrades the quality of preparation and interview performance. The eight to ten hours per week of dedicated preparation is manageable alongside full-time employment, especially with the structure provided by a clear preparation plan. Only quit first if continued employment is genuinely damaging the preparation effort.

4. Does an Infosys brand name help or hurt with product company applications?

It is neither a strong positive nor a strong negative. Product companies and GCCs are aware that IT services companies exist and that the technical work environment is different from a product company environment. The Infosys brand does not open doors at FAANG, but it does not close them either. What matters is the resume content, the preparation quality, and the interview performance. Engineers who have a strong Infosys background, combined with side projects, DSA practice, and quantified impact in the resume, are evaluated on those merits.

5. How do I handle the “Why are you leaving Infosys?” question in interviews?

Answer honestly and positively. Describe what you are seeking (product ownership, larger scale engineering challenges, building systems rather than maintaining them) rather than what you are escaping (boring projects, slow promotion, low salary). “I have valued the project delivery experience at Infosys, and I am now looking for a role where I can design systems from the ground up, have ownership of technical decisions, and work on products that I can directly see impacting users” is honest, professional, and positions the switch as a growth move rather than a flight.

6. Is a GCC better than an Indian product company for the transition?

It depends on the specific GCC and the specific Indian product company. A Goldman Sachs or Google GCC is a stronger platform than a mid-tier Indian startup. A Flipkart or Razorpay is a stronger platform than an average GCC at a manufacturing conglomerate. Evaluate each opportunity on the actual engineering environment, the growth trajectory, the compensation, and the quality of the team - not the category label.

7. Do I need to do competitive programming (Codeforces, etc.) or is LeetCode sufficient?

For most product company and GCC targets, LeetCode preparation is sufficient. Competitive programming platforms like Codeforces are more relevant for the absolute top tier (Google specifically has a reputation for harder problems) and for roles that specifically require competitive programming background. For Amazon, Microsoft India, mid-tier product companies, and most GCCs, consistent LeetCode Medium preparation is the appropriate target.

8. How important are certifications (AWS, etc.) for the transition?

Certifications are useful signals but not decisive factors in product company interviews. AWS Solutions Architect Associate, GCP Associate Cloud Engineer, or Azure Developer Associate certifications demonstrate initiative and cloud knowledge. They are worth pursuing as part of skill development and they improve the resume’s ATS keyword match. But they do not substitute for DSA preparation or system design knowledge - they are complementary, not alternative.

9. What if my Infosys project experience is entirely on legacy systems and has no modern stack exposure?

Side projects become even more important. Build personal projects using the modern stack relevant to the target role - a REST API deployed on AWS, a React application with a Node backend, a Python data pipeline on GCP. The side projects compensate for legacy project experience on the resume and demonstrate that the candidate has taken initiative to build modern skills independently. Mention these projects prominently and link to the GitHub repository.

10. Should I get an MBA to make the switch?

An MBA is generally not the right path for engineers who want to transition to product engineering roles. MBAs provide value for product management, business development, or consulting career transitions, but the technical tracks at product companies and GCCs do not require or particularly value an MBA. The investment of two years and significant money in an MBA is better spent on the technical preparation, side projects, and job search activities described in this guide for engineers whose goal is a technical individual contributor or technical lead role.

11. How do I handle salary negotiations when switching from IT services?

The standard negotiation challenge is that product companies and GCCs often ask for the current CTC and make an offer based on a percentage increase. The correct response is to provide the current CTC accurately (inflating it is dishonest and will surface in background verification) and simultaneously communicate the market rate for the target role: “My current CTC at Infosys is X, and based on my research of the market compensation for this role level at your company and peers, I am targeting Y.” Having a competing offer is the strongest negotiation position and is worth pursuing - even if you prefer one company, having an offer from another gives you factual negotiation leverage.

12. What is the best single resource for the IT services to product company transition?

There is no single best resource because the transition requires different resources for different components: LeetCode for DSA practice, “Designing Data-Intensive Applications” for system design foundations, the system design primer on GitHub for component-level knowledge, “Cracking the Coding Interview” for interview-specific preparation, and LinkedIn for networking and recruiter visibility. The meta-resource is this guide’s framework: honest assessment of the skill gap, structured closure of each gap component, resume rebuilding, and systematic application. Treat the transition as a project with defined phases and milestones, not as a wish that will materialise through passive hope.

13. How should I handle the gap between leaving Infosys (if I quit first) and joining a new company?

If for any reason you leave Infosys before securing a new offer - because of a hostile work environment, a project ending, or a personal decision - the gap period must be managed actively. Continue or intensify preparation. Take up freelance work or contract engagements to maintain professional activity on the resume. Contribute to open source. Be honest in interviews about the reason for the gap and the productive use of the time. Gaps of up to six months are generally acceptable if accompanied by evidence of active learning or professional activity. Gaps that are simply “took time off” with no activity signal reduced initiative to product company hiring managers.

The engineers who successfully transition from Infosys to product companies and GCCs are not uniformly the most talented engineers who passed through Infosys’s hiring process. They are the ones who accurately identified the gap between where they were and where they wanted to be, built a specific plan to close that gap, invested the consistent effort the plan required, and had the resilience to persist through failed interview attempts. The transition is achievable, the timeline is predictable, and the outcome - in compensation, technical challenge, and career growth - is worth the investment. The only thing standing between a current Infosys engineer and a product company career is the quality and consistency of the preparation.