The same engineer, with the same skills, can earn 4 LPA at one Indian company and 45 LPA at another. The difference isn't talent — it's the type of company. Services vs product. Startup vs enterprise. Pre-seed vs Series C vs FAANG. This is the lesson where you stop seeing "tech jobs" as one thing and start seeing the five very different worlds inside it — each with its own salary band, work culture, and growth ceiling.
A note on the numbers in this lesson. Indian salaries are quoted in LPA, lakhs per annum: one lakh is 100,000 rupees, so 12 LPA is about ₹1,200,000 a year. A crore is 100 lakh, written Cr, so "1 Cr" is about ₹10,000,000. The figures below are total compensation: salary plus bonus plus the value of any shares. They vary widely by city, company, and how well you negotiate.
Learning Objectives
After this lesson, you will be able to:
Explain the difference between services companies and product companies with real examples
Understand what startups and enterprises are, including how startups get funded from seed to IPO
Identify the major tech domains (fintech, healthtech, edtech, SaaS, and more) and what each one builds
Describe six common revenue models that tech companies use to make money
Know the basics of India's tech ecosystem -- the hubs, salary ranges, and global role
Your Reflection
Saves automatically
What’s one thing you learned? What’s still confusing?
There is no wrong path. Whether you end up at a massive services company or a tiny startup, you will learn, grow, and build things that matter. The goal right now is simply to understand the landscape so you can make an informed choice when the time comes.
The software industry can be split into two broad categories. Understanding this distinction is the single most important thing for anyone entering tech.
A services company builds software for other companies. They do not own the product. A bank in New York needs a new mobile app -- they hire TCS to build it. An insurance company in London needs to modernize their old systems -- they hire Infosys.
How they make money: It depends on the contract. On time-and-materials work the client pays for hours actually worked, so more people on the project means more revenue. On fixed-price work the firm has agreed one price for one scope, so more people means less margin, not more. Most large services firms run a mix of both, and which one your project sits on changes how the team reacts to a change request.
Staff augmentation, where a firm supplies individual engineers into a client's own team rather than owning a delivery, is a distinct arrangement. You will hear it called body shopping. It is a real part of the industry and not the same thing as time-and-materials delivery.
What it feels like to work there
You work on the client's product, not your own
Projects change every 6-18 months (variety, but less ownership)
Large teams with well-defined processes
Stable employment, predictable career ladder
Training programs for freshers (many hire straight from campus in bulk)
A product company builds its own product and sells it to users or businesses. Google builds Search. Spotify builds a music streaming platform. Stripe builds payment infrastructure. The company owns the product and earns revenue directly from it.
How they make money: Subscriptions, advertising, transaction fees, or licensing -- but always from their own product (more on revenue models in Section 4).
What it feels like to work there
You own what you build -- you see millions of users use your code
Deeper technical work (you live with the same codebase for years)
Smaller, more autonomous teams
Higher salaries (especially at top-tier product companies)
A startup is a small, young company trying to solve a problem in a new way. Startups are defined by uncertainty and speed. They do not have a proven business model yet -- they are searching for one.
Startups do not make money from day one. They need fuel to build the product before they can sell it. This fuel is funding from investors. Here is how the journey typically works:
The founders use their own savings to build the first version. No outside money. Total control, but limited resources. Zerodha famously bootstrapped its way to becoming India's largest stock broker without ever taking investor money.
The idea shows promise. Angel investors or early-stage venture capital (VC) funds invest a small amount to help the startup build its first product and get initial users. At this stage, the company might have 3-10 people.
The product has some users and early traction. VCs invest a larger amount to help the company grow its team, improve the product, and find product-market fit. Razorpay's Series A was $9 million in 2016.
The company has proven its business model and is scaling aggressively. Funding goes toward hiring, marketing, expanding to new markets, and outpacing competitors. Swiggy raised $100 million in its Series F round.
The company "goes public" -- its shares are listed on the stock exchange, and anyone can buy them. This is the big exit for early investors and employees with stock options. Freshworks became the first Indian SaaS company to IPO on NASDAQ in 2021. Zomato IPO'd on BSE/NSE the same year.
Built by two IIT Roorkee grads, became a unicorn (valued at $1B+) in 2020
Swiggy
Food and grocery delivery
2014
Started in Bangalore, now delivers in 500+ cities, IPO'd in 2024
Zerodha
Discount stock broker
2010
Bootstrapped (no VC money), profitable from year one, now India's largest broker
CRED
Credit card bill payments and rewards
2018
Founded by Kunal Shah, hit unicorn status in 3 years
Freshworks
SaaS for business (CRM, helpdesk)
2010
Started in Chennai, IPO'd on NASDAQ, valued at over $10B at peak
Something to Think About
There is no right answer here, and nothing is being marked. Pick the one that sounds most like you.
If you were starting your tech career tomorrow, which type of company would you prefer to work at first?
There is no wrong answer here. Your choice depends on your personality, financial situation, and goals. Many successful engineers have started at each of these and built great careers. The most important thing is to keep learning no matter where you are.
Software is not just one industry. It is a layer that sits on top of every industry. Here are the major domains where software companies operate, what they build, and what kinds of problems their engineers solve.
What they build: Digital payments, online banking, lending platforms, stock trading apps, insurance tech, cryptocurrency exchanges.
Example companies: Razorpay, Stripe, PayPal, Zerodha, PhonePe, Paytm, Square
Problems they solve: How do you process a payment in 200 milliseconds? How do you detect a fraudulent transaction among millions of legitimate ones? How do you let someone apply for a loan on their phone and get approved in 5 minutes?
Engineers they hire: Backend engineers (high-throughput systems), security engineers, data scientists (fraud detection), mobile developers.
Problems they solve: How do you connect a patient in a village with a specialist doctor in a city? How do you store millions of medical records securely? How do you use AI to detect diseases from X-ray images?
Engineers they hire: Full-stack developers, ML engineers (medical imaging), mobile developers, security engineers (health data is highly regulated).
What they build: Online courses, interactive learning platforms, test preparation apps, virtual classrooms, skill assessment tools.
Example companies: Coursera, Khan Academy, Unacademy, Physics Wallah, RugvAI Labs
Problems they solve: How do you make complex subjects (like machine learning) understandable through interactive visualizations? How do you personalize learning for millions of students with different skill levels? How do you keep learners engaged and motivated?
Engineers they hire: Frontend engineers (interactive UIs), content engineers, ML engineers (personalization), full-stack developers.
What they build: Online marketplaces, shopping apps, logistics and delivery systems, inventory management, recommendation engines.
Example companies: Amazon, Flipkart, Meesho, Myntra, Shopify, Nykaa
Problems they solve: How do you show the right product to the right person out of 100 million items? How do you deliver a package from a warehouse in Delhi to a home in Kerala in 2 days? How do you handle 10 million simultaneous users during a sale?
Engineers they hire: Backend engineers (scale), data scientists (recommendations), ML engineers, supply chain engineers, mobile developers.
What they build: Business tools that companies pay a monthly fee to use -- CRM, project management, communication, design tools, analytics.
Example companies: Slack, Notion, Salesforce, Freshworks, Zoho, Postman, Figma
Problems they solve: How do you build software that 10,000 different companies can use, each with their own needs? How do you ensure 99.99% uptime (less than 53 minutes of downtime per year)? How do you make complex business software feel simple?
Engineers they hire: Full-stack developers, platform engineers, DevOps/infrastructure, product engineers, API designers.
What they build: Video games, game engines, mobile games, AR/VR experiences, game streaming platforms.
Example companies: Unity, Epic Games (Unreal Engine), Riot Games, nCore Games (FAU-G), Supercell
Problems they solve: How do you render a 3D world at 60 frames per second? How do you synchronize multiplayer game state across players on different continents? How do you make an AI opponent that is challenging but not frustrating?
Engineers they hire: Game developers (C++, C#), graphics programmers, network engineers, AI engineers (game AI), mobile developers.
Problems they solve: How do you detect a hacker among millions of legitimate users? How do you protect sensitive data from being stolen? How do you respond to a security breach in real time?
Engineers they hire: Security engineers, penetration testers, ML engineers (anomaly detection), backend engineers, cryptography specialists.
You met six revenue models in the previous lesson: licences, subscriptions,
billable services, transactions and usage, advertising and freemium, and
support contracts. Rather than list a different six here, two additions are
worth making now that you know about startups and investors.
Freemium deserves separating from advertising, because it is a different
bet. The product is free below a threshold and paid above it: Slack above a
certain team size, Zoom above forty minutes, Dropbox above a storage limit. It
works because free users do the marketing, and it fails when the free tier is
generous enough that nobody upgrades.
Marketplace or commission did not appear at all. The platform takes a cut
of transactions between two other parties: Amazon on seller fees, Swiggy on
restaurant commissions, Airbnb on both host and guest. The platform owns no
inventory, which is why marketplaces scale quickly and why they are so hard to
start, since you need both sides before either side is useful.
The reason investors care which model a company runs is the shape of the
revenue over time. A subscription business knows roughly what next month looks
like. A marketplace does not know until both sides turn up. That difference is
most of what "is this a good business" means in a funding conversation.
Chapter 1 (1990s-2000s): The Outsourcing Era. Companies like TCS, Infosys, and Wipro grew massive by providing IT services to Western companies at lower costs. India became the "back office of the world." This created millions of jobs and established India's reputation for engineering talent.
Chapter 2 (2010s): The Startup Boom. Indian founders started building products for the Indian market -- Flipkart took on Amazon, Ola took on Uber, Paytm built a digital payment ecosystem. Venture capital poured in. India produced over 100 unicorns (companies valued at $1B+).
Chapter 3 (2020s-Now): Global Product Builders. Indian companies are now building products for the world, not just India. Freshworks sells to companies in 120+ countries. Postman (API tools) is used by 30 million+ developers globally. Zerodha pioneered the discount brokerage model. Indian engineers are founding companies in Silicon Valley and leading teams at every major tech company.
Figures are indicative. Actual numbers vary by company, role, city, and
#Reading a Job Offer Like a Pro (Beyond Just Salary)
When you get your first offer, do not just look at the LPA number on the top line. Here are the questions that matter — most candidates forget to ask them:
1. What is the breakdown? Base, variable, RSUs, ESOPs, joining bonus?
A "30 LPA" offer might be 18 base + 4 variable bonus + 6 RSUs vested over 4 years + 2 joining bonus. The cash you see this year is closer to 22 LPA, and the 8 LPA of "stock comp" depends on the stock price and the vesting cliff. Always ask for the four-year vesting schedule.
2. What is the "cliff"?
Most startup stock options have a 1-year cliff — meaning if you leave before 1 year, you get nothing. If you leave at 11 months, you walk away with zero equity. Plan accordingly.
3. What is the strike price (for ESOPs)?
If the company's fair market value is ₹100/share and your strike price is ₹100, your options are worth nothing the day you receive them. They only become valuable if the share price goes up. Joining late at a "late-stage" startup means your strike price is already high, which caps your upside.
4. What is the dilution risk?
A startup with 1% of equity for you sounds great. But if the company raises 3 more rounds, your stake gets diluted. By the time of IPO, that 1% might be 0.4%. Always ask: "What is my fully-diluted ownership percentage?"
5. What is on-call expected to look like?
Some teams page you twice a year. Some page you weekly. The same role at two companies can be very different lifestyles. Ask the team members directly — not the recruiter.
6. Hybrid? Remote? In-office?
Bangalore traffic alone can cost you 2 hours/day. The salary delta between a fully-remote startup and a 5-day-office FAANG often disappears once you compute the time cost. Time is the actual currency.
Before joining a startup, do this 15-minute due diligence:
Funding stage and last round date. If they raised a Series B in 2022 and have been silent since, they may be burning runway. Check Crunchbase or Tracxn.
Headcount trend. LinkedIn shows employee count over time. Flat or shrinking is a yellow flag. Rapidly growing is a green flag — but ask why.
Founder profile. Do they ship? Founders who are active on Twitter/LinkedIn talking about real product details usually run real companies. Founders who only post inspirational quotes — be careful.
Glassdoor. Read the 1-star reviews carefully. Patterns matter more than individual rants.
Talk to ex-employees. A 20-minute call with someone who left in the last year tells you more than 5 hours of interviews.
The COVID-19 pandemic permanently changed how Indian tech works:
Before 2020: Almost everyone went to office. Remote work was rare and seen as unprofessional.
2020-2022: Forced remote work. Companies realized productivity did not drop. Many engineers moved back to their hometowns.
2023-Now: Hybrid is the new normal. Most companies do 2-3 days in office, rest from home. Fully remote roles exist but are less common. Some companies (like Zerodha and Postman) remain remote-first.
Remote work has opened up opportunities for engineers in Tier 2 and Tier 3 cities to work at top companies without relocating to expensive metro cities.
Services companies build software for clients; product companies build their own -- both are valid paths, but they offer very different work experiences
Startups are high-risk, high-reward; enterprises are stable and structured -- funding goes from bootstrapped to seed to Series A/B/C to IPO
Software powers every industry -- fintech, healthtech, edtech, e-commerce, SaaS, gaming, and cybersecurity are just a few of the many domains where engineers work
Tech companies make money through six main models -- subscription, advertising, transaction fees, freemium, enterprise licenses, and marketplace commissions
India's tech ecosystem is evolving from outsourcing to building global products -- Bangalore, Hyderabad, Pune, and Chennai are the major hubs, and salaries at top product companies are competitive globally
Quick Check1 / 5
A company has 50,000 employees and builds custom software for banks, airlines, and insurance companies worldwide. They bill clients based on the number of engineers assigned to each project. Is this a services company or a product company?
Next: Tech Roles and Career Paths. You now know the kinds of company. The next lesson is the kinds of person inside them: what eight different roles actually do on a Tuesday, and which one sounds like something you would enjoy. After that comes the how — the actual process by which a team takes "we should add a chat feature" and turns it into 50 million people sending messages. Sprints. Standups. Pull requests. CI/CD. The day-one playbook your future team will assume you already know.