AI Agent Engineer, APAC

Who we are

Looking for a career that will excite, challenge and inspire you? Thinking about insurance? Perhaps you should. Working for us is a totally different experience to what you probably expect. How do you feel about the things you truly love? Don’t you want to protect them in the best way possible? Imagine if you could help people do this all over the world.

You’d give them confidence and reassurance by protecting what they love most. This is no easy task. In today’s interconnected world, tackling risk is fast, unpredictable and invigorating. You’ll have to think on your feet as you manage risks big and small, from flooding to cyber‑crime. You’ll be tackling issues like these in over 170 countries. It’s a big challenge, but you’ll have a truly diverse network helping you.

As part of an international team, every day would provide opportunities to learn, grow and share ideas.

As you make an impact across borders, you’ll feel the support of being part of a strong and stable company. A long‑standing player in the insurance industry, we make every effort to address the career development needs and plans of our employees to ensure their success in the future.

So make a difference. Be challenged. Be inspired. Be supported, Love what you do. Work for us.

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.

We are building the next‑generation Generative

AI platform solution that will power multiple business lines and connect to upstream and downstream systems.

As our Senior Data Engineer/Data Architect 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.

• Architecture & Design
• Design AI Agents with MCP/API interface
• 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.
• Identifying the right fit‑for‑purpose LLM model
• Hands‑on Engineering
• Write production‑grade code
• Build ingestion pipelines, retrieval‑augmented‑generation (RAG) services, micro‑services, and CI/CD workflows.
• Conduct code reviews, performance tuning, and zero‑downtime releases.
• Run and monitor large‑scale AI workloads in the cloud (Azure/AWS).
• Delivery Leadership
• 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.
• Mentoring & Culture
• Coach engineers on best practices in data engineering, Dev Ops, and LLM‑Ops
• Foster a “get‑stuff‑done” culture—passion, autonomy, accountability.

As an LLM Engineer your skills and qualifications will ideally include:

• Strong engineering experience building data platforms or large‑scale distributed systems, with proven experience in cloud‑native AI / ML workloads via automated CI/CD pipelines
• Strong experience in Python
• Demonstrate hands‑on experience in designing, developing, and maintaining APIs, with expertise in building scalable and efficient solutions using FastAPI.
• Proven delivery of GenAI / LLM products in production: RAG pipelines, vector databases (Pinecone, Milvus, FAISS, etc.), Lang Chain/ Llama Index/ Lang Graph…