AI Engineering Intern

Who We Are

Zurich is one of the world's leading multi-line insurers, serving people and businesses across more than 200 countries and territories for over 150 years. We protect communities against some of the most complex and fast-moving risks of our time, including climate change reshaping entire economies and technology fundamentally altering how people live and work.

In APAC, our regional AI team sits at the heart of this transformation. We are a small, ambitious group embedded within a global institution. The tools we build reach millions of customers, are stress-tested against real data, and must be operational. We collaborate directly with business stakeholders to take ideas from whiteboard to production, building AI solutions that make a measurable impact. We are determined to shape a future where communities stay resilient, and we believe AI, built responsibly and engineered well, is a big part of how we get there.

The Role

Your code will reach real users, on day one.

• Design and build agentic AI systems that handle multi-step reasoning, tool use, and autonomous decision-making across real business workflows.
• Develop AI-powered applications using large language models, including prompt engineering and RAG pipelines.
• Build and deploy AI-driven solutions using a mix of frameworks and approaches including FastAPI, Celery, and other task orchestration patterns, containerized with Docker and shipped via GitHub Actions.
• Integrate agents with structured and unstructured data sources, equipping them with the right tools, memory, and retrieval layers to operate reliably.
• Collaborate with business stakeholders to map existing workflows and re-engineer them as agentic solutions that reduce manual effort and surface better decisions.
• Architect and scale solutions on Azure for production use.
• Monitor, evaluate, and iterate on deployed AI systems, treating observability as a first-class concern.

Qualifications

Skills & Experience

Ongoing or completed bachelor's or master's degree in Computer Science, Mathematics, Data Science, or a related field. We care most about your ability to drive solutions from idea to delivery — the rest we can work with.

Core Skills

• Python
• LLMs
• Data Science
• Data Wrangling
• Business Communication

Nice to Have (Skills you can expect to develop in this role)

• Azure
• GitHub CI/CD
• Context Engineering
• Solution Architecture
• Experience handling both structured and unstructured data (SQL, NoSQL, free text, images, web data).
• Familiarity with agent engineering patterns: tool use, memory, multi-agent orchestration, and evaluation.

Projects that delivered measurable value are a big plus — bring something you can walk through end to end.

What You Will Gain

• Production Impact: Your code reaches real customers across APAC markets, running in production from day one.
• Agentic AI at Scale: Build multi-step reasoning systems and GenAI pipelines that run against real business problems.
• Enterprise Cloud: Hands-on Azure at scale, with real compliance constraints that teach you things a side project never will.
• Direct Stakeholder Access: You'll sit in on real business conversations and shape solutions from the start.