Software Engineer - AI

About the role

A fast-growing fintech company based in Singapore builds credit and financial products for underserved individuals and small businesses. Its AI Transformation team is building an internal platform that helps employees use AI effectively and develop software faster, covering an agentic AI work platform, AI-driven SDLC automation and a centralised knowledge base. This is a hands-on software engineering role where you own parts of the platform from design and implementation through deployment and operation.

Key responsibilities

• Build production AI applications and services, including backend services, APIs, integrations and LLM-powered agent workflows.
• Own delivery end to end: clarify requirements, design pragmatically, write maintainable code and tests, deploy safely, operate and troubleshoot production systems.
• Use agentic AI coding tools to prototype and accelerate development while keeping design, security and production quality in hand.
• Measure and improve quality with tests, traces, observability, user feedback and LLM or agent evaluations.
• Turn successful patterns into documented platform components usable by other teams.
• Work with engineers, product, security, data scientists and business teams, considering security, data protection and change management.

Required profile

• 3+ years of professional software engineering experience, including hands-on Python development of backend services or APIs.
• Experience designing, deploying and operating backend services or platform capabilities in production.
• Ability to break down ambiguous problems, weigh trade-offs and communicate decisions clearly.

Required skills

• 2+ years with a relational database such as PostgreSQL or MySQL, including schema design, SQL querying, indexing and query performance tuning.
• 2+ years deploying, operating and monitoring services on AWS or GCP, using Docker or Kubernetes and CI/CD pipelines.
• Hands-on experience building LLM-powered applications with agents, tools and multi-step workflows (RAG, prompt management, LangGraph/LangChain, Strands).
• Experience using AI coding agents such as Claude Code or Codex.

Good to have: a CS or software engineering degree; experience scaling an LLM platform to 1,000+ users; knowledge of frontier LLM tooling (MCP/A2A, model routing, streaming); experience building knowledge-access systems; production model development and serving (SFT, LoRA, vLLM); startup or early-stage product experience.