imc Software Engineer Interview: Questions & Prep (2026)

IMC is a global proprietary trading and market-making firm, known for building ultra-low-latency systems that power its trading operations across equities, options, and derivatives markets worldwide. Software engineers at IMC typically work on order management systems, market data infrastructure, execution platforms, and internal tooling for quantitative strategies. India offices are commonly in Hyderabad and Mumbai, with teams focused on both core trading infrastructure and software platform engineering.

Candidates report a multi-stage process that typically includes an online coding screen, followed by two to three technical rounds covering data structures, algorithms, concurrency, and systems design. A final round typically adds behavioral and team-fit questions. C++ and Python are the languages most commonly tested, and the firm places heavy emphasis on performance-aware thinking at every stage.

As of July 2026, knok's radar shows 162 open Software Engineer roles at IMC. The broader Software Engineer market across India has 5,395 openings right now, so you have a strong pipeline to work in parallel. Market salary bands run 6-12 LPA at entry level, 15-25 LPA at mid-level, 28-45 LPA for senior roles, and 40-65+ LPA for lead or staff positions. Trading firms like IMC are publicly reported to offer compensation above these standard market bands.

These questions are drawn from candidate reports and commonly cited resources for trading-firm software engineer interviews. Expect coding problems on a shared screen with an interviewer watching your approach in real time.

1. Implement an LRU (Least Recently Used) cache with O(1) get and O(1) put. Walk through your choice of data structures and explain why.
2. Design an order book that supports add order, cancel order, and efficient best-bid and best-ask queries.
3. Explain the difference between a process and a thread. How do you prevent a race condition on a shared counter?
4. Write a thread-safe singleton in C++. What is wrong with the naive double-checked locking approach before C++11?
5. Given a stream of stock prices, compute the maximum profit from a single buy followed by a single sell.
6. Explain RAII in C++. When would you choose unique_ptr over shared_ptr, and why?
7. TCP vs UDP: explain the trade-offs and describe a trading-system scenario where you would pick each one.
8. You discover a deadlock in a multi-threaded trading system. Walk through how you would diagnose it and what code changes you would make.
9. Implement a function to find the kth largest element in an unsorted array. Discuss the trade-off between sorting, a min-heap, and Quickselect.
10. Design a rate limiter for an internal API that serves live market data to multiple downstream consumers.
11. A function that was fast enough in development is now unacceptably slow under production load. Walk through how you would investigate and fix this.
12. Tell me about a time you caught a serious bug before it reached production. What did you do?

Q: Tell me about a time you fixed a serious performance issue in production code.

*Situation:* Our market data normalisation service was consistently spiking in latency during peak trading hours, causing downstream alerts to fire repeatedly.

*Task:* I was responsible for identifying the root cause and shipping a fix quickly, because every additional millisecond of delay had a direct impact on the trading desk.

*Action:* I profiled the service and found that the hot path was allocating a new map on every incoming tick. I replaced it with a pre-allocated flat array indexed by instrument ID and added a fast-path cache for the most active symbols. I wrote unit tests to verify correctness, then ran a load test in staging before deploying to production.

*Result:* Peak-hour latency dropped significantly, confirmed by the metrics on our internal dashboard. The on-call alert never fired again for that service during my time on the team.

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Q: Tell me about a time you had to learn a new technology quickly under pressure.

*Situation:* My team was asked to integrate with an external exchange that only supported a binary FIX protocol we had never worked with before, and we had a tight deadline.

*Task:* I volunteered to own the integration because I had the most networking background on the team, even though I had not used that specific protocol before.

*Action:* I read the exchange's full technical specification in the first few days, wrote a minimal C++ parser with test coverage for all the message types we needed, then pair-programmed with a colleague to review edge cases. I gave the team lead a daily update so there were no surprises near the deadline.

*Result:* We shipped the integration ahead of schedule. The exchange certified our implementation on the first submission, which the certification team mentioned was uncommon.

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Q: Describe a situation where you disagreed with a teammate on a technical approach.

*Situation:* A senior colleague wanted to use a lock-based queue to pass messages between threads in a latency-sensitive path. I believed a lock-free ring buffer would perform significantly better.

*Task:* I needed to make my case clearly without creating conflict, and the team needed to reach a decision quickly to stay on schedule.

*Action:* Rather than debating in a meeting, I wrote a benchmark comparing both approaches under realistic load. I shared the results alongside a short document explaining the trade-offs, including the added complexity of the lock-free version.

*Result:* The team decided to use the lock-free ring buffer for the hot path and the lock-based queue for lower-frequency control messages. The decision was grounded in data, and my colleague appreciated that I had done the work to prove the point rather than just assert it.

STAR for behavioral questions. Structure every behavioral answer as Situation (what was happening), Task (what you were responsible for), Action (what you specifically did), and Result (what changed). Keep each part to two or three sentences. Interviewers at trading firms often probe hardest on the Action step, so be specific about the technical choices you made, not just the outcome.

Think-aloud for coding questions. Candidates report that IMC interviewers want to hear your reasoning as you code, not just the final answer. Before writing any code, state your approach, the data structures you plan to use, and the time and space complexity you are targeting. If you spot a suboptimal first approach, call it out and explain why you are shifting to a better one.

Trade-off framing for design questions. For any systems design question, follow this structure: clarify requirements, sketch the high-level design, then walk through the key trade-offs (latency vs throughput, consistency vs availability, simplicity vs performance). Trading firms care deeply about the reasoning behind design choices, not just the design itself.

The bug hunt framework. If asked about debugging or incident scenarios, use this structure: observe the symptoms, form a hypothesis, collect evidence (logs, profiler output, metrics), isolate the variable, apply the fix, and verify. This maps directly to how on-call engineers at trading firms actually work.

Performance-first thinking. IMC builds systems where speed matters at every layer. Interviewers look for candidates who naturally ask 'what is the latency requirement?' and 'where is the bottleneck?' before writing code. Mentioning Big-O complexity is expected; what stands out is knowing when a theoretically slower algorithm is practically faster due to cache locality or branch prediction.

Concurrency fluency. Almost every role involves multi-threaded systems. Candidates report being asked about mutexes, condition variables, atomics, and lock-free data structures. Be ready to explain what a memory model is and why it matters in C++11 and later.

Clean, readable code under pressure. Correctness comes first, then clarity. Interviewers do not expect an elegant solution in the first few minutes, but they do expect you to refactor toward clarity once the logic is correct. Use meaningful variable names even in a timed interview.

Intellectual honesty. If you do not know something, say so and reason from first principles. Candidates report that guessing or bluffing is a quick path to rejection at IMC. Saying 'I am not certain of the exact syntax, but the approach would be...' is respected far more than a confident wrong answer.

Ownership mindset. Behavioral answers that show you spotted a problem, took initiative without being told, and saw it through to resolution tend to resonate. Avoid answers where everything was a team effort with no clear individual contribution from you.

Weeks 1 to 2: Core algorithms and data structures. Focus on hash maps, heaps, trees, graphs, and arrays. Solve problems at medium to hard difficulty on a competitive coding platform with a timer. Prioritise problems that appear in trading-firm interview lists, which are commonly cited in public forums like Blind and LeetCode Discuss.

Week 3: Systems and concurrency. Review threads, mutexes, condition variables, atomics, and lock-free programming. Implement a thread-safe queue from scratch. Practice explaining memory models out loud, not just on paper.

Week 4: C++ depth. Review RAII, smart pointers, move semantics, and templates. Be ready to write correct C++ in an interview. Review common undefined behaviour traps such as signed integer overflow and dangling references.

Throughout: Python fluency. IMC uses Python for scripting, data analysis, and some strategy tooling. Make sure you can write clean Python quickly, handle standard library usage comfortably, and explain the GIL when asked.

Mock interviews. Candidates report that the biggest prep gap is not knowledge but communication under pressure. Do several mock interviews with a peer or on a practice platform, coding out loud and explaining your thought process the whole time.

Company context. Understand what market making means and why latency matters to IMC's business. Read publicly available material on how exchanges work and what a bid-ask spread is. You do not need quant finance expertise for an engineering role, but context sharpens both your answers and your end-of-round questions.

knok checks 150+ job sites nightly, applies to roles that match your resume, and messages HR on your behalf, so your applications keep moving while you are heads-down preparing.

Jumping straight to code. The most common mistake candidates report is writing code before clarifying the problem. Take a moment to ask about edge cases, input size, and constraints. Interviewers at IMC often penalise silent coders who dive in without thinking aloud.

Ignoring time and space complexity. Stating the complexity of your solution is expected at every step, not just at the end. If your solution is quadratic, say so and explain whether that is acceptable given the constraints before moving on.

Vague behavioral answers. Answers like 'we worked together as a team' tell interviewers nothing useful. Every behavioral answer needs a specific action you personally took and a measurable or observable result that followed.

Overclaiming C++ depth. Candidates sometimes list C++ as a core strength and then cannot explain the difference between stack and heap allocation or write a correct copy constructor. Be honest about your depth; interviewers will probe quickly and the gap becomes obvious.

Not asking questions at the end. Interviewers at trading firms expect genuine curiosity about the work. Prepare a few questions about the team's current engineering challenges or the tools they use. Generic questions like 'what is the culture like' leave little impression.

Freezing on unknown questions. If you do not know the answer, narrate your reasoning out loud. Interviewers are often more interested in how you think through an unfamiliar problem than in whether you happen to have memorised the answer.