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

Seek is one of Asia Pacific's largest employment marketplaces, powering job search and hiring for employers and candidates across the region. Their engineering teams build search relevance, recommendation engines, and large-scale data pipelines that serve millions of users. As of July 2026, Seek has 70 Software Engineer openings, reflecting active hiring across their technology organisation.

The interview process typically spans several stages. Candidates report an initial recruiter or HR screening call, followed by one or more technical rounds covering coding and system design, and a final round with behavioral questions from a senior engineer or hiring manager. The exact format can vary by team and seniority, so treat this as a general picture based on what candidates typically experience.

Software Engineer salaries at Seek align broadly with wider market rates. The table below shows typical ranges across experience levels.

Actual compensation varies by team, location, and negotiation. Always verify current figures on Glassdoor or levels.fyi before accepting an offer.

Based on what Software Engineer candidates typically report from Seek interviews, these questions come up most often.

1. How would you design a job recommendation engine that serves millions of users every day?
2. Walk me through how you would improve the relevance of a job search engine. What signals would you use?
3. Tell me about a time you diagnosed and fixed a performance problem in a production system.
4. Describe a project where you had to coordinate across multiple teams to ship a feature on time.
5. How do you approach building a system that needs to be highly available while keeping data consistent?
6. Tell me about a time you disagreed with a technical decision your team was moving toward. What happened?
7. How would you design the backend for an employer dashboard that shows real-time applicant activity?
8. What is your experience with REST or GraphQL APIs? Walk me through a non-trivial API you designed.
9. Tell me about a time you took ownership of a problem that was not originally yours to solve.
10. How do you keep your technical skills current? What have you learned or built in the past year?
11. Describe a situation where you had to make a technical trade-off under a tight deadline. How did you decide?
12. How would you approach personalising job search results for candidates without compromising their privacy?

Use the STAR format for all behavioral questions: Situation, Task, Action, Result. Keep the Situation and Task brief. Spend the most time on Action, since that is where you show what you personally did and how you thought through the problem.

Q: Tell me about a time you fixed a performance problem in a production system.

*Situation:* A key API endpoint used by our mobile app was responding very slowly during peak traffic hours, causing visible loading delays for users.

*Task:* I was asked to investigate and resolve the issue without taking the service offline.

*Action:* I added query profiling to the endpoint and found an N+1 query problem introduced during a recent feature addition. I rewrote the query using a join, added a composite index on the most-filtered columns, and introduced a short-lived cache for data that rarely changes.

*Result:* Response time dropped sharply. The mobile team confirmed a clear improvement in user experience, and the fix held through subsequent traffic peaks without regression.

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Q: Describe a time you worked across teams to deliver a feature.

*Situation:* We were building a notification system that required input from the backend platform team, the frontend team, and the data team for event tracking.

*Task:* I was the backend engineer responsible for the API contracts and the push notification service.

*Action:* I drafted API specs early and ran a short alignment session with each team to surface blockers before they became problems. I built versioned endpoints so the frontend team could test against staging while I was still finalising business logic. I agreed on an event schema with the data team upfront so analytics would be live from day one.

*Result:* The feature shipped on schedule with no integration issues at launch. The data team began reporting on notification engagement immediately, and the product team used those insights in the next planning cycle.

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Q: Tell me about a time you made a technical trade-off under pressure.

*Situation:* We had a firm product deadline for a new search filter feature, but the cleanest solution required refactoring a core module that would take weeks.

*Task:* As the engineer leading the feature, I had to decide whether to push back on the timeline or find a more pragmatic path.

*Action:* I proposed a two-phase approach: ship a working implementation using a targeted workaround that met the product requirements, paired with a scheduled refactor in the next sprint. I documented the technical debt clearly in our tracker and got explicit sign-off from the engineering manager so the follow-up work was protected.

*Result:* We shipped on time. The workaround caused no user-facing issues during that window, and the refactor completed as planned in the following sprint.

For behavioral questions: STAR

STAR stands for Situation, Task, Action, Result. Keep Situation and Task brief. Spend the most time on Action: what you personally did, the reasoning behind your choices, and any obstacles you navigated. Close with a concrete Result. Avoid vague actions like 'I helped the team' and weak closings like 'it went well.' Be specific about your contribution and what actually changed.

For system design questions: Clarify first, then build

Before drawing any component boxes, ask clarifying questions. Who are the users? What is the expected scale? What are the consistency and availability requirements? Then walk through your design top-down: API layer, business logic, data storage, async processing if needed. Call out trade-offs at each step rather than waiting for the interviewer to probe.

For coding questions: Think aloud throughout

State your approach before writing any code. Mention time and space complexity as you go. Handle edge cases out loud. If a brute-force solution comes to mind first, say so, then explain how you would optimise it. Candidates typically report that Seek interviewers care as much about your reasoning process as about the final working answer.

Seek's engineering work centres on search relevance, large-scale data processing, and product features that serve a very large and diverse user base. Interviewers are typically looking for a combination of technical depth, clear communication, and demonstrated ownership.

Technical depth: Can you design a system that handles real scale? Can you write clean, correct code and reason about its complexity? Do you understand trade-offs between different storage or processing approaches?

Ownership and impact: Interviewers at Seek typically want to hear about impact, not just activity. 'I implemented feature X' is weaker than 'I identified the bottleneck, proposed the approach, built it, and the outcome was Y.' Use 'I' rather than 'we' when describing your specific contribution.

Collaboration: Much of Seek's engineering work involves coordination across product, data, and platform teams. Candidates who demonstrate a clear track record of working well across functions tend to stand out.

Curiosity: Given Seek's focus on AI-driven matching and personalisation, interviewers often probe whether you actively follow relevant developments and apply what you learn in your day-to-day work.

Week 1: Coding fundamentals

Practise data structures and algorithms covering arrays, strings, trees, graphs, and dynamic programming. Aim for clean, readable solutions rather than just passing tests. Practice explaining your approach out loud as you code, since this is what interviewers observe.

Week 2: System design

Study how large-scale search and recommendation systems are built. Key concepts to cover: caching strategies, message queues, database indexing and sharding, horizontal scaling, and consistency trade-offs. Sketch a few end-to-end designs relevant to Seek: a job search backend, a notification service, or a real-time applicant analytics pipeline.

Week 3: Behavioral preparation

Write out STAR stories for at least six situations from your own experience: a performance win, a cross-team collaboration, a conflict or disagreement, a time you took ownership outside your role, a time you learned something new quickly, and a situation where you made a hard technical trade-off.

Week 4: Mock interviews and research

Do timed mock sessions for both coding and system design. Read about Seek's products so you can connect your answers to challenges that are genuinely relevant to them. Prepare two or three thoughtful questions to ask your interviewers. On the application side, knok checks 150+ job sites nightly, applies to Software Engineer roles that match your resume, and messages HR on your behalf, so your applications keep moving while you focus on preparation.

1. Jumping straight into code. Always discuss your approach first. Interviewers want to see how you think, not just whether you can produce a working answer.

1. Saying 'we' throughout. Use 'I' when describing your specific contribution. 'We built the system' tells the interviewer nothing about what you did.

1. Skipping clarifying questions in system design. Assuming scale, consistency requirements, or user behaviour without asking makes your design look unfocused and generic.

1. Ignoring behavioral preparation. Behavioral rounds typically carry significant weight. Arriving with no prepared STAR stories is a common and costly mistake.

1. Giving vague results. 'The team was happy' or 'it went well' are weak closings. Anchor your result to something concrete: a metric improved, a deadline met, a decision unblocked.

1. Not having questions for the interviewer. Candidates who ask nothing signal low engagement. Prepare at least two questions about the team, the technical challenges they are working on, or how success is measured in the role.