Claroty Software Engineer Interview: Questions, Experience & Prep (2026)

Claroty is a cybersecurity company that specialises in securing operational technology (OT), IoT, and industrial control systems for critical infrastructure. Their platform gives enterprises visibility into connected assets across factories, hospitals, energy grids, and logistics networks. Engineers at Claroty work on problems like network protocol analysis, passive asset discovery, vulnerability management, and large-scale security telemetry pipelines.

As of July 2026, Claroty has 17 open Software Engineer roles. The interview process typically involves a recruiter screen, one or more coding rounds, a system design discussion, and a final round with engineering leadership. Candidates report a strong emphasis on security thinking, distributed systems comfort, and familiarity with domain-specific industrial protocols.

Salary bands for Software Engineers in India (knok jobradar data, July 2026):

These figures reflect the broader Software Engineer market in India. Claroty's specific offers depend on role, location, and your experience level.

These questions come up frequently in Claroty Software Engineer interviews, based on candidate reports and the company's product focus on OT/IoT security:

1. Walk me through how you would design a system to passively discover and classify OT/IoT assets across a large enterprise network.
2. How would you build a high-throughput pipeline to ingest and analyse raw network traffic data in near real time?
3. Describe a project where you worked within strict security or compliance constraints. How did those constraints shape your design choices?
4. How would you design a vulnerability correlation engine that maps CVEs to specific industrial devices and prioritises them by risk?
5. Explain your approach to building a multi-tenant SaaS platform where strict tenant data isolation is a hard requirement.
6. What is your experience with parsing binary network protocols, and how do you safely handle untrusted or malformed input?
7. How do you design for fault tolerance in a distributed system where components can go offline without warning?
8. Describe your experience running containerised workloads in production. What challenges did you face with Kubernetes at scale?
9. How would you build an alert-ranking or alert-deduplication system to reduce 'alert fatigue' for a security operations team?
10. Tell me about a hard production bug you diagnosed. Walk me through your debugging process step by step.
11. How do you decide when to slow down and refactor versus shipping quickly in a product that directly affects customer security?
12. Industrial protocols like Modbus, DNP3, and BACnet are central to Claroty's product. How would you approach learning and safely implementing parsers for unfamiliar protocols?

Q: Walk me through how you would design a system to passively discover and classify OT/IoT assets on an enterprise network.

*Situation:* At my previous company, a manufacturing client's factory network had grown over a decade with no central asset inventory. Devices ranged from modern PLCs to legacy sensors, and nobody knew exactly what was connected.

*Task:* I was asked to design a discovery system that could identify assets without sending any active probes, since active scanning can crash fragile industrial equipment.

*Action:* I proposed a passive network tap that mirrored traffic to a dedicated analysis cluster. I built an ingestion pipeline using a message queue to buffer incoming packets, and wrote protocol fingerprinting modules that identified device types from traffic signatures. For classification, I created a lightweight model trained on publicly available OT device datasets to assign device categories and confidence scores. I also designed the fingerprinting rules to be updatable without redeploying the core pipeline.

*Result:* Within two weeks of deployment, the system surfaced a large number of previously untracked devices. The client's security team was able to reduce their mean time to detect anomalies, and the passive-only design meant zero disruption to production systems.

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Q: Tell me about a hard production bug you diagnosed. Walk me through your process.

*Situation:* We were running a distributed event-processing service that occasionally dropped security alerts under high load. The bug was intermittent and produced no useful stack trace in our logs.

*Task:* My task was to find the root cause without taking the service offline, since it processed time-sensitive alerts.

*Action:* I added structured logging around every queue hand-off point so we could trace individual events end-to-end. I then used distributed tracing to correlate where events entered the system but did not exit. After collecting data over two days, I found that a consumer thread was occasionally holding a lock while calling an external enrichment API with variable latency. Under load, this caused a backpressure cascade. I refactored the enrichment call to be asynchronous and added a circuit breaker with a fallback to a local cache.

*Result:* Event drop rate went to zero in testing and held at zero after the production deployment. We also added a latency SLO on the enrichment API as a long-term safeguard.

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Q: How do you balance feature delivery speed with code quality in a security product?

*Situation:* At a startup I worked at, the product team wanted a new detection rule editor shipped in two weeks for a major customer demo. The existing rule engine had no test coverage.

*Task:* I needed to ship the feature on time without introducing regressions that could cause missed detections, which in a security product has real consequences.

*Action:* I negotiated with the PM to spend the first three days writing a minimal test harness for the rule engine before touching the new feature. I used property-based testing to cover edge cases quickly rather than writing many individual unit tests. I kept the feature's scope small: a simple DSL that compiled down to the existing rule format, rather than rewriting the engine itself.

*Result:* We shipped on time. The test harness caught two pre-existing bugs we had not known about. The PM later credited the 'no surprises' delivery as a factor in the customer signing the contract.

For system design questions, use a four-step structure. Start by clarifying requirements (scale, latency, consistency needs). Then sketch high-level components and data flow. Next, dive into the hardest part of the design, usually the piece most relevant to security or OT constraints. Finally, discuss trade-offs and what you would change at a larger scale. At Claroty, always factor in the safety constraint: active probing can harm industrial equipment, so passive-first designs are often the right call.

For behavioral questions, use STAR: Situation (brief context), Task (your specific responsibility), Action (what you personally did, not the team), Result (measurable or clearly positive outcome). Keep Situation and Task short. Spend most of your time on Action and Result. Claroty interviewers are looking for ownership, so use 'I' rather than 'we' when describing your decisions.

For security-specific questions, think in three layers: prevention, detection, and response. If asked how you would secure a system, cover what you would do to prevent compromise, how you would detect a breach if prevention fails, and how you would limit blast radius. This structured thinking signals security maturity even without a dedicated security background.

For protocol and domain questions, if you are unfamiliar with the specific protocol being asked about, say so honestly and then walk through how you would approach learning it: read the RFC or public specification, find open-source implementations, write a minimal parser, and fuzz it with malformed input to find edge cases. Candidates who can articulate a clear learning process reassure interviewers more than those who bluff familiarity.

Claroty builds security products for environments where mistakes can affect physical safety, not just data. Interviewers are looking for a few specific signals:

Security-first thinking. Can you identify the security implications of your own design choices? You do not need to be a penetration tester, but you should instinctively ask questions like: 'What happens if an attacker controls this input?' or 'How do we limit what a compromised component can access?'

Comfort with constraints. OT environments are unusual. You often cannot restart a machine, cannot send active probes, and must work with legacy protocols alongside modern cloud APIs. Candidates who treat these constraints as interesting engineering challenges rather than frustrations stand out.

Systems thinking at scale. Claroty processes large volumes of network telemetry. Interviewers want to see that you understand the cost of design choices: memory layout, serialisation overhead, lock contention, backpressure. You do not need to memorise benchmarks, but you should reason clearly about bottlenecks.

Honest communication. Candidates report that Claroty interviewers respond well to 'I am not sure, but here is how I would find out' and poorly to confident-but-wrong answers. The company works in a domain with real-world safety stakes, so intellectual honesty is valued highly.

Curiosity about the domain. You do not need to arrive as an OT security expert. Showing that you have read about how industrial control systems differ from enterprise IT, and that you find that difference genuinely interesting, signals that you will grow well into the role.

Week 1: Foundations and domain context.

Review data structures, algorithms, and system design fundamentals. Focus specifically on distributed systems concepts: consistency models, event-driven architectures, and fault tolerance patterns. Read publicly available material on how OT networks differ from enterprise IT networks (air gaps, legacy protocols, safety-critical constraints). Skim the Wikipedia articles or RFCs for Modbus and DNP3 so you can speak to them at a basic level in an interview.

Week 2: Company-specific preparation.

Read Claroty's publicly available research reports and blog posts. They publish threat intelligence on OT vulnerabilities, which doubles as a window into the engineering problems the product team is solving. Practice designing a passive network monitoring system and a multi-tenant SaaS platform (these themes appear frequently in candidate reports). Write out your top three or four career stories in STAR format, making sure each one shows a clear technical decision and its outcome.

Week 3: Practice and mock interviews.

Do timed coding practice, focusing on graph algorithms, sliding window problems, and concurrency. Practice explaining system designs out loud, since Claroty interviewers typically want a conversation rather than a monologue. Record yourself answering two or three behavioral questions and check whether your answers stay focused on your own actions. Prepare two or three questions to ask the interviewer about engineering challenges specific to the OT security domain.

The week of your interview.

Review the job description and map your experience to each listed requirement. Prepare your 'tell me about yourself' answer to fit within two minutes. If the interview is remote, test your setup the day before. Know the interviewer's name and team if that information was shared in advance.

Skipping the security lens on design questions. A candidate who designs a system without considering what happens when a component is compromised signals a blind spot that matters a lot at a security company. Always include at least one comment on trust boundaries and what you would do if one were violated.

Over-engineering to impress. Claroty interviewers report that candidates sometimes propose unnecessarily complex architectures to show range. A simple design you can defend clearly beats a distributed microservices diagram you struggle to explain.

Treating OT constraints as irrelevant. If you dismiss the 'you cannot probe active devices' constraint as a minor detail, interviewers will notice. These constraints are central to the product's value proposition.

Vague STAR answers. Saying 'we improved system performance' without a concrete outcome leaves the interviewer with nothing to evaluate. Always end a behavioral answer with a specific result, even if it is qualitative.

Asking no questions at the end. Candidates who ask nothing come across as uninterested or unprepared. Prepare two or three genuine questions about the team's current engineering challenges or the product roadmap.

Bluffing domain knowledge. If you do not know what DNP3 is, say so and explain how you would learn it. Interviewers in this space can tell when a candidate is bluffing, and it damages trust for the rest of the conversation.