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

Persistent Systems is a Pune-headquartered technology company known for software product engineering, cloud transformation, and digital services for ISVs, SaaS companies, and large enterprises, primarily in North America and Europe. If you are preparing for a Software Engineer interview here, expect a process that rewards both strong coding fundamentals and a product-oriented mindset.

Candidates typically report a process of three to four rounds: an online coding assessment, one or two technical rounds covering data structures, algorithms, and (for mid-to-senior roles) system design, and a final HR or managerial conversation. Process details vary by team, so treat this as a general guide and confirm specifics with your recruiter.

As of July 2026, Persistent has 5 open Software Engineer roles. The broader Software Engineer market across India stands at 5,395 open positions, with Bangalore leading at 776 listings.

These questions reflect patterns candidates report from Persistent interviews and the themes visible in Persistent's public job descriptions.

1. Walk us through your experience working on a software product end to end, from design to delivery.
2. How do you break a large feature into smaller, testable units of work?
3. Describe a time you worked on migrating a legacy system to a modern stack. What were the biggest challenges?
4. How do you balance shipping new features with managing technical debt?
5. Persistent works with many ISV and SaaS clients. How do you ramp up quickly on an unfamiliar codebase or domain?
6. Describe your hands-on experience with a cloud platform such as AWS, Azure, or GCP in a production environment.
7. How do you approach writing unit and integration tests, and how do you decide what to prioritize?
8. Tell me about a time you had to collaborate with a distributed or client-side team across time zones.
9. How would you design a scalable REST API for a product serving thousands of concurrent users?
10. What is your approach to code reviews, both as a reviewer and when your own code is being reviewed?
11. Persistent talks about 'digital engineering'. What does that mean to you, and how have you applied it in a past role?
12. How do you evaluate new technologies and decide which ones are actually worth adopting on a project?

Q: How do you balance shipping new features with managing technical debt?

*Situation:* I was on a backend team at a mid-size SaaS startup. The codebase had grown quickly over two years and had several modules with no test coverage and tightly coupled dependencies.

*Task:* My manager wanted new API endpoints delivered in the same sprint where I had identified a critical refactor needed in the auth module.

*Action:* I mapped out which parts of the auth module the new endpoints would actually touch. I refactored only those specific paths, wrote unit tests for them, and built the new endpoints on top of the cleaned-up code. I documented the remaining debt in our backlog with a short note explaining the risk if left unaddressed.

*Result:* The new endpoints shipped on time, the auth module had test coverage for the first time, and the team adopted a habit of tagging debt items with risk labels. The following quarter, we cleared the remaining debt in a planned sprint.

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Q: Describe a time you worked on migrating a legacy system to a modern stack.

*Situation:* A client project involved a monolithic Java EE application handling order processing for a retail company. It was slow to deploy and difficult to scale during peak sales periods.

*Task:* I was part of a small team responsible for migrating the order service to a microservices architecture on AWS.

*Action:* We used the strangler fig pattern, extracting one bounded context at a time rather than rewriting everything at once. I owned the inventory and order-status services, built them as Spring Boot microservices with REST APIs, set up CI/CD pipelines, and wrote contract tests so the legacy system and new services could run side by side during cutover.

*Result:* The migration took roughly six months. Deployment time for the order service dropped significantly, and the team could scale individual services during high-traffic periods without touching the rest of the monolith.

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Q: How do you ramp up quickly on an unfamiliar codebase or domain?

*Situation:* I joined a fintech project mid-cycle at a previous employer. The codebase was large and I had no prior domain exposure.

*Task:* I needed to contribute a working feature within my first two weeks.

*Action:* I started by reading the README and any architecture decision records. Then I traced one complete user flow through the code, from the API layer down to the database, taking notes along the way. I asked my team lead for a short walkthrough of the most confusing parts, and before writing any code, I submitted a small bug fix to understand the PR and review process.

*Result:* I shipped my first feature in the second week. Later I shared this approach with new joiners on the same team and it became an informal onboarding guide.

For coding and algorithm questions, think aloud from the start. State the brute-force approach first, then explain why you want to optimize. Walk through time and space complexity before writing any code. Interviewers at product engineering companies like Persistent care as much about your reasoning process as the final solution.

For system design questions, use a four-step structure: clarify requirements (scale, constraints, non-functional needs), sketch a high-level diagram, deep-dive into one or two components the interviewer is most interested in, then discuss trade-offs. Avoid jumping to a specific technology before you have understood the problem fully.

For behavioural questions, use the STAR format (Situation, Task, Action, Result) with a strong emphasis on the Result. Persistent interviewers typically want to see ownership and follow-through, so close your answer with what changed or improved, not just what you did.

For client or stakeholder scenarios, show that you can translate technical decisions into plain language. If asked how you would handle a technical delay with a client, frame your answer around setting expectations early, offering options, and keeping the working relationship intact.

Product mindset over task execution. Persistent positions itself as a product engineering company. Interviewers want to see that you think about user impact, long-term maintainability, and business outcomes, not just completing assigned tickets.

Ownership and follow-through. Candidates who describe work they saw all the way to production, including monitoring and post-launch fixes, consistently stand out. Stopping your answer at 'I wrote the code and handed it off' is rarely enough.

Client collaboration skills. A significant part of Persistent's work involves engineering alongside client teams. Be ready to share examples of communicating technical constraints or trade-offs to non-technical stakeholders or cross-functional partners.

Ability to ramp up fast. Persistent rotates engineers across client projects, so interviewers value candidates who can describe a structured, repeatable approach to learning new domains, codebases, or stacks quickly.

Code quality and testing habits. Expect questions or live coding exercises where testability matters. Familiarity with CI/CD practices and code review culture is a strong advantage, especially at the mid-to-senior level.

Week 1: Foundations and company research
Review data structures and algorithms at a level matching your target role. Entry-level candidates (0-2 years) should be comfortable with arrays, linked lists, trees, and basic dynamic programming. Mid-to-senior candidates should also cover graph algorithms and system design basics. Read Persistent's recent blog posts and case studies to understand the domains they work in, such as healthcare IT, banking technology, and hi-tech ISV products.

Week 2: Coding practice and system design
Solve a few problems daily, focusing on patterns such as sliding window, two-pointer, and BFS/DFS rather than memorising individual solutions. For mid-to-senior roles, practice designing one system per day: a URL shortener, a notification service, or a ride-sharing backend. Sketch your diagrams by hand and explain trade-offs out loud to build fluency.

Week 3: Behavioural prep and mock interviews
Write out five or six STAR stories covering ownership under pressure, technical conflict resolution, fast ramp-up on a new project, and a time something went wrong and how you fixed it. Practice saying them aloud so they sound natural rather than rehearsed. Do at least two mock interviews with a peer or a live feedback service before your actual interview.

In the final days, review the job description line by line and map your experience to each requirement. Prepare two or three specific questions to ask your interviewer about the team, the current tech stack, and how success is measured in the role.

Jumping to code before clarifying the problem. Many candidates start typing the moment a coding question is read out. Taking a moment to ask about edge cases and constraints almost always leads to a better solution and signals strong engineering habits.

Generic behavioural answers. Saying 'I am a team player' or 'I always deliver on time' without a specific story is a red flag for interviewers. Every behavioural answer needs a concrete example with a clear, measurable outcome.

Ignoring testability in design or coding questions. Persistent cares about code that can be maintained and tested. If you design a system or write code without mentioning how you would test it, you leave easy marks on the table.

Over-engineering system design. Candidates sometimes propose the most complex distributed architecture possible to appear knowledgeable. Interviewers want to see you reason about what the actual problem needs, not showcase the biggest-company playbook.

Not asking questions at the end. Saying 'I have no questions' signals low interest. Prepare at least two specific questions about the team's current work or engineering culture.

Underplaying client-facing experience. At Persistent, working well with external stakeholders is genuinely valued. If you have experience presenting to clients or managing expectations during a delivery, bring it up proactively.