Data Engineer jobs in Singapore

We are building the next‑generation GenerativeAI platform solution that will power multiple business lines and connect to upstream and downstream systems.

As our Data Engineer you will own the end‑to‑end design and delivery of this platform—architecting, coding, shipping, and scaling it in production in coordination with our Data Scientists. This is a hands‑on leadership role: we are looking for builders, not slide‑makers.

Shape the overall data & GenAI architecture (batch / streaming pipelines, vector stores, feature stores, LLM‑Ops tooling, API layer).

Select frameworks, storage engines, orchestration tools, and security patterns that will stand the test of scale and time.

Conduct code reviews, performance tuning, and zero‑downtime releases.

Run and monitor large‑scale AI workloads in the cloud (Azure/AWS).

Lead multi‑component projects.

Break down epics, estimate effort, and remove blockers for the squad.

Report progress and trade‑offs directly to senior business & tech stakeholders.

Coach engineers on best practices in data engineering, DevOps, and LLM‑Ops.

As a Data Engineer your skills and qualifications will ideally include:

8+ years building data platforms or large‑scale distributed systems, with at least 3 years in cloud‑native AI / ML workloads.

Proven delivery of GenAI / LLM products in production: RAG pipelines, vector databases (Pinecone, Milvus, FAISS, etc.), LangChain/LlamaIndex/LangChain or equivalent, prompt orchestration, fine‑tuning, and model monitoring.

Mastery of modern data tooling: SQL & NoSQL stores, Docker, Terraform, GitHub Actions/AzureDevOps.

Strong grasp of data governance, security, and privacy for regulated industries (insurance / financial services a plus).

Design and implement systems for managing agent long‑ and short‑term memory, including structured logging of interactions and collection of user feedback, to support continuous learning and performance improvement using technologies such as Azure Redis or PostgreSQL

Develop and enforce app and user‑level authorization and authentication mechanisms for agent APIs to ensure secure data access and prevent unauthorized exposure across business units.

Track record of sticky retention—you build, iterate, and scale products over several years.

Experience with AI Agents Observability & Performance Monitoring: reporting on key performance metrics to maintain reliability and optimize outcomes.

Excellent communication skills; able to translate architectural trade‑offs to both engineers and executives.

Experience with Model Context Protocol (MCP) workflows, standardization of AI‑driven tool calling and workflows.

Zurich Insurance has the policy to be an equal opportunity employer. We aim to attract and retain the best qualified individuals available, without regard to criteria such as race/ethnicity, national origin, religion, gender, sexual orientation, age or disability.

At Zurich we believe that having a culture of inclusion is essential in delivering good results. Attracting, retaining and developing a diverse workforce where employees feel valued, respected and empowered allows people to reach their full potential. As a business this diversity helps us to better reflect and understand our 4 million customers’ needs to allow us to drive better outcomes. As a global organisation, with an increasingly agile workforce, we’re happy to consider flexible working arrangements.