The Foundation: More Than Just Code
For years, the formula for Indian tech interviews was clear: master Data Structures and Algorithms (DSA). While DSA remains a crucial baseline, the goalposts have moved, especially for senior roles. Top product companies and FAANG offices in Bangalore,
Hyderabad, and beyond are increasingly focused on system design. They are no longer just asking, "Can you code?" They are asking, "Can you think?" This means evaluating how you approach ambiguity, communicate trade-offs, and make decisions with imperfect information. The interview is less of a test and more of a conversation to see how you would operate as a colleague. It's a shift from being a pure coder to becoming a well-rounded engineer who understands the business and user context.
Prompt 1: The AI Integration Challenge
Expect prompts like: "Design an AI-powered feature to recommend books," or "How would you use AI to improve content moderation on a social platform?" These questions are not really about your knowledge of specific machine learning models. Interviewers are testing your product thinking. A great answer starts with clarifying questions: Who is the user? What problem are we solving for them? How do we measure success? You should then discuss the user experience, considering the probabilistic nature of AI. For example, what happens when the AI is wrong? How do you build user trust? You should also be able to discuss the data pipeline at a high level—how would you gather training data, and what are the potential biases to watch out for? This shows you can think end-to-end, from user problem to responsible implementation.
Prompt 2: The 'Scale for Bharat' Scenario
A common prompt in the Indian context is designing a system for massive scale, often with a focus on cost-efficiency and resilience in lower-connectivity environments. Think: "Design a system like Hotstar to handle 50 million concurrent users during a cricket match," or "Architect a hyperlocal delivery service for Tier-3 cities." The key here is to go beyond generic scaling advice like "add more servers." Talk specifics. Discuss the merits of SQL vs. NoSQL databases, the use of a Content Delivery Network (CDN) to reduce latency, and implementing robust caching strategies with tools like Redis or Memcached. Mentioning real-world Indian examples and their architectural challenges—like UPI's transaction volume or Flipkart's Big Billion Day sales—shows you understand the unique context of building for the next billion users. The first question to ask should be about the business goal, as that will shape your technical trade-offs.
Prompt 3: The Cost-Optimisation Puzzle
Another uniquely Indian spin on system design is the focus on cost. You might be asked: "We have a service with high cloud bills. How would you architect a solution to reduce costs by 30% without significantly impacting performance?" This prompt tests your commercial awareness. A strong answer involves analyzing the existing architecture to find the most expensive components. Is it database reads, network egress, or GPU compute for a machine learning model? Your solution should then propose specific, practical trade-offs. Could you use a cheaper storage tier for older data? Can you implement more aggressive caching to reduce database load? Or perhaps switch to a serverless architecture for spiky workloads? Discussing these trade-offs—for example, accepting slightly higher latency for non-critical features in exchange for lower costs—proves you can make pragmatic engineering decisions that align with business objectives.
Prompt 4: The Vague Business Goal
Sometimes the prompt is intentionally ambiguous: "Design a news feed for a social app," or "Build a URL shortening service." The biggest mistake is to jump straight into drawing boxes and arrows. The entire point of this exercise is to see if you can scope the problem yourself. A senior engineer's first job is to seek clarity. Spend the first few minutes asking clarifying questions to establish functional and non-functional requirements. For a news feed, ask: "Is it chronological or algorithmic? Will it support images and videos? What's more important, low latency or strong consistency?" For a URL shortener, ask: "What is the expected read/write ratio? Do the links need to be editable?" This initial dialogue demonstrates maturity and proves you can translate a business need into a technical plan, which is often more valuable than memorizing a specific architecture.
