Cigna Software Engineer Interview: Questions & Prep (2026)

Cigna Technology India builds and maintains digital health platforms, claims processing systems, and analytics tools serving global health members. As of July 2026, Cigna has 46 open Software Engineer roles in India, making it one of the more active healthcare-tech hirers right now.

The interview process typically runs 3-4 rounds: an online coding assessment, one or two technical sessions covering data structures and system design, and a behavioral discussion. Candidates report the full cycle taking 2-4 weeks. Cigna teams commonly work with Java or Python backends, REST APIs, microservices on AWS or Azure, and healthcare data standards like HL7 or FHIR.

Salary expectations for SWE roles across the Indian market: entry-level (0-2 years) falls in the 6-12 LPA band, mid-level (3-5 years) in 15-25 LPA, senior (6-9 years) in 28-45 LPA, and lead or staff engineers at 40-65+ LPA. Glassdoor submissions from Cigna employees suggest compensation is commonly cited toward the upper half of the mid and senior bands.

1. Tell us about yourself and why you want to work at Cigna specifically.
2. Describe a time you worked on a system that handled sensitive or regulated data.
3. How would you design a REST API for a claims submission service that needs to handle high traffic?
4. Walk us through a complex bug you found and fixed in a production system.
5. How do you approach writing testable, maintainable code in a large codebase?
6. How would you handle a microservice that is intermittently failing in production?
7. Have you worked with healthcare data standards such as HL7 or FHIR? Walk us through your experience.
8. How do you prioritize tasks when working on multiple features with competing deadlines?
9. Describe a time you disagreed with a technical decision your team made. How did you handle it?
10. Given a large dataset of insurance claims, how would you design a pipeline to detect duplicate or potentially fraudulent entries?
11. How do you approach performance optimization in a database-heavy application?
12. Tell us about a time you had to learn a new technology quickly to deliver a project on time.

Q: Walk us through a complex bug you found and fixed in a production system.

*Situation:* Our healthcare claims API was intermittently returning server errors for roughly one in every few hundred requests. The issue did not appear in staging and only showed up under production load.

*Task:* I was the on-call engineer and needed to identify the root cause and resolve it without taking the service offline, since it was processing live insurance claims.

*Action:* I added granular structured logging around the database connection pool and correlated timestamps with our cloud monitoring dashboards. I discovered that connection timeouts spiked whenever batch jobs ran on a fixed schedule. I updated the pool configuration to set a shorter acquire timeout, added a retry with exponential backoff, and moved the batch jobs to low-traffic windows.

*Result:* The error rate dropped to near zero within one deployment. We also added an alert for connection pool saturation so the team could catch similar issues proactively in future.

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Q: How do you prioritize tasks when working on multiple features with competing deadlines?

*Situation:* At my previous role I was assigned three parallel tasks: a new patient portal feature, a performance fix for a reporting module, and a security patch for an authentication flow.

*Task:* All three had been flagged as high priority by different stakeholders, and I needed to sequence them without missing any commitments.

*Action:* I scheduled a short sync with my engineering manager and product owner to share an honest assessment of effort and risk. We agreed the security patch carried the highest risk if delayed, so I completed it first. I then unblocked a colleague who could pick up the portal feature while I worked on the reporting fix, and kept all three stakeholders updated daily via a shared tracking board.

*Result:* All three items shipped within the original sprint. The security patch went out three days early, and the experience led our team to adopt a standard triage process for competing priorities.

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Q: Tell us about a time you had to learn a new technology quickly to deliver a project.

*Situation:* Our team was asked to integrate a third-party claims adjudication service that communicated over FHIR R4 APIs. No one on the team had hands-on FHIR experience at the time.

*Task:* I volunteered to own the integration and had two weeks before a client demo.

*Action:* I spent the first two days reading the FHIR R4 specification and setting up a sandbox with an open-source FHIR server. I paired with a senior architect for two code review sessions to validate my approach, then built a lightweight adapter in Java that translated our internal data model to FHIR resources and added contract tests to catch any spec drift.

*Result:* The integration was demo-ready on day eleven. The adapter layer became a reusable internal library that two other teams adopted over the following quarter.

For DSA questions (online assessment): Read the problem twice before writing any code. State your brute-force approach first, then reason toward an optimal solution. Explain time and space complexity at each step. Candidates report Cigna's assessments lean toward arrays, strings, hashmaps, and tree traversals, with occasional dynamic programming problems.

For system design: Use this structure: clarify functional requirements, state your assumptions (traffic, data size), outline your components and APIs, discuss edge cases, then do a deep dive on one component the interviewer selects. For Cigna, anchor your designs around reliability and data privacy, since the systems touch health records.

For behavioral questions: Use STAR (Situation, Task, Action, Result). Keep Situation and Task combined brief. Spend the most time on Action, focusing on your individual contribution, not the team's. Close with a concrete Result. A qualitative outcome with clear context ('reduced on-call incidents noticeably across a system handling millions of claims') is better than no result at all.

For 'why Cigna' questions: Tie your answer to their healthcare mission rather than generic company praise. Mention their focus on digital health tools, preventive care data platforms, or the specific team's work. Hiring managers, candidates report, respond best to engineers who can articulate the downstream impact of their code on real patients and members.

Domain awareness. Cigna wants engineers who understand (or are genuinely curious about) healthcare data, privacy regulations, and the downstream impact of software on patients. You do not need to be a domain expert. Showing you have read up on HIPAA or claims processing principles goes a long way.

Code quality, not just correctness. Candidates report that interviewers ask follow-up questions about testing, edge cases, and maintainability even after a working solution is on the board. Think about what you would add given more time.

Communication under ambiguity. Healthcare systems are complex and requirements shift. Interviewers want to see you ask clarifying questions, state assumptions clearly, and adjust your approach as new constraints emerge.

Ownership mindset. Cigna values engineers who take problems to completion, including monitoring, alerting, and documentation, not just the initial implementation. Reference examples from your past where you owned something from design all the way to production.

Week 1: Technical foundations

1. Solve one DSA problem daily, focusing on arrays, strings, binary trees, and graphs.
2. Review system design basics: load balancing, caching, database indexing, API rate limiting, and message queues.
3. Read a brief overview of HIPAA compliance and FHIR as a healthcare data standard. Candidates report that even surface-level awareness impresses Cigna interviewers.

Week 2: Company and role-specific prep

1. Read Cigna's publicly available technology blogs and digital health reports to understand what they are building.
2. Prepare 5-6 STAR stories covering: debugging production issues, cross-team collaboration, learning a new technology, handling disagreements, and delivering under pressure.
3. Practice explaining your past projects in 2-3 minutes each, ending with measurable impact.
4. Do two mock system design sessions with a peer who can push back on your assumptions.

Day before the interview

1. Re-read the job description and map your experience to each listed requirement.
2. Prepare two specific questions for the interviewer about the team's tech stack, on-call practices, or product roadmap.
3. If it is a remote interview, test your audio, video, and screen-sharing setup in advance.

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1. Jumping into code without clarifying the problem. Spend 2-3 minutes on requirements and edge cases before writing any syntax. Interviewers typically evaluate your thinking process, not just the final answer.

1. Ignoring the healthcare context. Generic answers that could apply to any tech company miss an opportunity. Connect your responses to reliability, data integrity, and patient impact wherever you can.

1. Vague STAR answers. Saying 'we improved performance' without context weakens your case. Use numbers where you have them. If you don't, describe the scale and the stakes so the interviewer can gauge the impact.

1. Skipping the Result. Many candidates describe what they did but forget to close the loop. Always end with what happened and, ideally, what changed or what you learned because of your work.

1. Over-engineering system design. Candidates report that Cigna interviewers prefer a clean, explainable design over a maximally complex one. Start simple. Add components only when prompted or when you can clearly justify the need.

1. Not asking questions at the end. Staying silent signals low interest. Prepare two specific questions about the team or the product. Asking about on-call practices or the team's current technical challenges shows you are thinking seriously about joining.