Senior / Software Engineer
shopback-2 · Singapore, Singapore ·
- Work mode
- Onsite
- Seniority
- Senior
- Employment
- Full time
- Category
- Software engineering
shopback-2 · Singapore, Singapore ·
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At ShopBack, AI is how we build. It is not a side tool. You will ship products with AI agents as teammates, and you will build the systems that make those agents fast, secure, and reliable.
Both fresh graduates and experienced engineers are welcomed to apply.
Turn repeated work into reusable AI assets. You build skills, tools, MCP servers, and agent workflows that your whole team uses every day, so you do not write one-off prompts that nobody can reuse.
Make AI output measurable. You build evals, tests, and guardrails so that we can trust what agents produce. "It looks right" is not enough.
Build loops, not tasks. You connect agents to CI, code review, observability, and incident data so the system gets better each time it runs.
Design clean, scalable services. You build the APIs and backend services behind our apps, payments, and partner integrations.
Find where AI changes the product itself. You work with product, data, and design on ideas that go beyond changing how we build.
Explain trade-offs clearly. You analyse requirements, propose solutions, and say when AI is the wrong tool.
Raise the bar. You lead projects, mentor engineers, and share what works so the whole org becomes more AI-native
Strong fundamentals. You know system design, data structures, testing, and debugging. AI makes good engineers better. It does not replace fundamentals.
Proof that you applied AI, not only used it. Show us something you built.
Healthy scepticism. You treat AI output like code from a new teammate. You review, verify, and test it.
Production experience. You have built and run services in the cloud. Experience with consumer-facing products is a plus.
Learning velocity. You pick up new tools fast, and you drop old habits when a better tool arrives.
Fresh graduates: side projects, hackathons, internships, and open source all count. Send us the repo.
You built agent infrastructure at scale: sandboxes, runtimes, orchestration, or permission models.
You designed LLM-as-judge or eval pipelines that the team trusts.
You shipped AI features to real users and handled cost, latency, and failure modes.
You put AI into the SDLC: automated MR review, test generation, or incident triage.
Delivery & Ops: GitLab CI, Datadog
Data: Redshift, Spark, S3
AI: Claude Code/Codex, MCP
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