Senior / Software Engineer

Job description

### **Our Journey** The ShopBack Group is Asia-Pacific's leading shopping and rewards platform, trusted by over 20 million active members across 13 markets, including Germany and the United States. Driven by the vision to make every day more rewarding, ShopBack saves members money and time with more ways to earn and more to do with what they earn, and empowers merchants and brand partners to effectively engage its members. Founded in Singapore in 2014, ShopBack now powers over US$5.5 billion in annual sales and half a million transactions a day for more than 20,000 online and in-store partners. ## **About the Role:** 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.** ### What You'll Own - Own features end to end. You take a feature from idea to design, build, test, ship, and operate. You use AI to move faster at every step, and you stay accountable for the result. - 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 ### Essentials to Succeed - 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. ### Bonus Points - 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. ### Technologies We Use & Love - Core: TypeScript / Node.js, React, Postgres, Kafka, SQS, Kubernetes on AWS, Knative, Debezium - 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.