Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.
ShopBack is seeking AI-focused engineers in Singapore to build fast, secure, and reliable AI-powered systems. You will ship products with AI agents, create reusable AI assets, and design scalable services powering our apps, payments, and partner integrations.
We welcome both fresh grads and experienced engineers. You’ll work with product, data, and design to push AI-forward and mentor teammates, strengthening the org’s AI-native capabilities.
The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 20 million active members across 13 markets. In 2025, the Group continued its global growth with its expansion into North America. Driven by the vision to make every day more rewarding, ShopBack is dedicated to saving members money and time, and delivering delight every day. The platform also enables merchants and brands to engage with their members in a cost-effective manner. Founded in 2014, ShopBack now powers over US$5.5 billion in annual sales for over 20,000 online and in-store partners, and has rewarded shoppers with more than US$900 million (over S$1 billion) in Cashback to date. Through its innovative offerings, ShopBack continues to create value for both members and merchants. Notably, its payment solution, ShopBack Pay, offers members a convenient and rewarding payment option at checkout.
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
We care more about how fast you learn a stack than about which stack you already know.