Lead Platform Engineer

Location: Singapore

Department: Technology

As a Lead Platform Engineer you’ll design, build and operate the GenAI Platform Services that will support AI use-cases across the bank.

Key responsibilities

Build and operate GenAI Platform Services across key service groups the platform is organised around. For example:

· Orchestration — Agent Runtime, Workflow Orchestration, Tool Calling, Agent Identity.

· Evaluation — Online Evaluation, Offline Evaluations, Red Teaming, A/B Experimentation.

· Model Gateway & Registry — Model Gateway, Cost Metering, Agent Registry.

· RAG & Memory — Embedding Pipeline, Vector Store, Short-Term Memory, Long-Term Memory.

Provide paved-road build and release tooling so that agents, prompts, evals and models are built, versioned, tested and promoted through a single "golden path".

Gate every release on evaluation. Build capabilities to enable offline evaluations and LLM-graded evals, red-team suites and A/B experimentation into the release pipeline as enforced quality gates — no capability reaches production without passing them.

Build automated governance controls into the platform Support in implementing common capabilities to enable guardrails / monitoring, access control, audit logging and Model Risk Management as default behaviours of the platform primitives.

Enable the FDE and AI Operations teams with SDKs, templates, documentation and reference implementations, and fold their production learnings back into the platform roadmap.

Required skills & experience

• 10+ years of software engineering background with production ownership of platform, infrastructure or developer-tooling services.
• Experienced in Cloud Native technologies such as - AWS, Kubernetes, terraform
• Hands-on CI/CD and build-system experience: reproducible builds,artifact registries, promotion/rollback, policy-as-code gates.
• A platform-as-a-product mindset— you build for internal consumers and measure adoption, lead time and reliability, not lines of code.
• Comfort working in a regulated environment where security, governance, auditability and risk management are non-negotiable.

Role Specific Technical Competencies

• Experience with cloud GPU/inference serving and auto-scaled model hosting.
• Exposure to financial-services and banking and AI governance/guardrail tooling.
• Experience building self-service developer platforms or "golden paths" adopted by other teams.
• Familiarity with GenAI / LLM building blocks: model gateways / routing, RAG and vector stores, agent/tool orchestration, and evaluation (offline evals, red teaming, A/B testing).