Frequently Asked Questions
Everything you need to know about product-based companies in India, salaries, interviews, and career growth.
1 Getting Started
What is a product-based company?
A product-based company builds and sells its own software products or services directly to customers. Examples include Flipkart, Razorpay, Swiggy, and Zoho.
Unlike service companies (TCS, Infosys, Wipro) that work on client projects, product companies focus on their own products, offering:
- Better engineering culture and practices
- Higher salaries (2-3x more)
- More ownership and impact
- Modern tech stacks
- Stock options / ESOPs
What is the salary difference between product and service companies?
Product companies typically pay 2-3x more than service companies:
| Experience | Service Company | Product Company |
|---|---|---|
| Fresher (0-1 yr) | Rs. 3-5 LPA | Rs. 8-25 LPA |
| Mid-level (3-5 yr) | Rs. 8-15 LPA | Rs. 25-50 LPA |
| Senior (6+ yr) | Rs. 15-25 LPA | Rs. 50-80+ LPA |
2 Career Transition
How do I transition from a service company to a product company?
The transition typically takes 6-12 months of dedicated preparation:
- Master DSA: Solve 200+ LeetCode problems (medium/hard focus)
- Build projects: Create 2-3 impressive side projects on GitHub
- Learn System Design: For roles with 2+ years experience
- Contribute to open source: Shows initiative and collaboration
- Network: Connect with product company employees on LinkedIn
- Apply directly: Use company career pages, not just job portals
Which product companies hire freshers in India?
Many product companies actively hire freshers:
Most hire through campus placements and off-campus drives.
3 Interview Preparation
What is the interview process at product companies?
Most product companies follow this process (2-4 weeks total):
- Online Assessment: 2-3 DSA problems (60-90 mins)
- Phone Screen: 1-2 coding rounds with engineer
- Onsite/Virtual rounds:
- DSA rounds (2-3)
- System Design (for 3+ years exp)
- Machine Coding (build project in 1-2 hrs)
- Hiring Manager round
FAANG companies may have 5-6 rounds. Startups often have 3-4 rounds.
What is machine coding round in interviews?
Machine coding is a practical round where you build a working application in 1-2 hours. Common problems:
- Snake & Ladder game
- Parking Lot management system
- Splitwise expense tracker
- In-memory cache (like Redis)
- Task scheduler / Job queue
- Tic-Tac-Toe with AI
You're evaluated on:
- Working solution
- Code quality and readability
- Design patterns (SOLID principles)
- Extensibility of code
- Edge case handling
Practice LLD (Low-Level Design) problems on GitHub repos.
How many LeetCode problems should I solve?
Quality matters more than quantity.
- Indian unicorns: 150-200 problems (medium focus)
- FAANG/Big Tech: 300+ problems (medium + hard)
- Startups: 100-150 problems often enough
Recommended approach:
- 70% medium difficulty
- 20% hard difficulty
- 10% easy (for warm-up)
Use Blind 75 or NeetCode 150 as starting points. Understand patterns, don't memorize solutions.
What skills are required for product company jobs?
Core technical skills:
- Strong DSA fundamentals
- Proficiency in 1-2 languages (Java, Python, C++, JavaScript)
- Databases and SQL
- Git version control
- Basic networking concepts
For senior roles (3+ years):
- System Design (HLD)
- Microservices architecture
- Cloud platforms (AWS/GCP/Azure)
- CI/CD pipelines
Soft skills:
- Problem-solving mindset
- Clear communication
- Agile team collaboration
4 Location & Remote Work
Which city is best for product company jobs in India?
Do product companies offer remote work?
Many companies now offer remote or hybrid options:
Note: Remote roles may pay 10-20% less than Bangalore on-site salaries. Check individual company policies.
5 AI & Future of Work
How is AI changing software engineering jobs?
AI coding assistants like Claude Code, GitHub Copilot, and Cursor are transforming how developers work:
Skills that matter MORE:
- Problem decomposition & clear thinking
- System design & architecture
- Code review & critical analysis
- Domain expertise & business context
- Communication (with AI and humans)
Skills that matter LESS:
- Syntax memorization
- Writing boilerplate code
- API documentation lookup
Key insight: AI amplifies good engineers. Focus on judgment, architecture, and understanding - not typing speed.
Should I learn AI/ML to stay relevant as a developer?
You don't need to become an ML engineer, but understanding AI tools is now essential:
For all developers:
- Learn to use AI coding assistants (Claude Code, Copilot, Cursor)
- Understand basics of how LLMs work
- Practice writing effective prompts
- Know limitations and when to verify AI output
For AI/ML career path:
- Strong Python and math fundamentals
- ML courses (Andrew Ng, fast.ai)
- Cloud platforms (AWS/GCP ML services)
- Build projects with real datasets
Do companies allow AI tools in interviews?
Interview practices are evolving. Here's the current landscape:
AI-Allowed (Growing)
- Take-home projects
- Real-world simulation exercises
- Some system design rounds
- Pair programming with AI
AI-Prohibited (Still Common)
- Live DSA coding (proctored)
- Whiteboard system design
- Behavioral interviews
- Code review exercises
Tip: Still practice DSA without AI - many companies use traditional coding rounds. But also practice using AI tools effectively - it shows modern workflow skills.
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