We Are Waiting for You
Hi there
I am
Álvaro Gallego,
the recruiter for this position. Nice to meet you
First, a little bit about what I like the most about working at
Zurich Technology Delivery Center
: The environment here is incredibly collaborative and innovative. Our tech-driven mindset fosters continuous learning and growth, creating an atmosphere where everyone can thrive.
Now, I can't wait to share this exciting journey with you at
Zurich

First of all, THANK YOU for considering our company. We understand that finding the right opportunity can be tough, but I'll try to make it easier.
Who Are We?
Let me introduce us. You're reading about
Zurich Insurance Group
, a global leader in insurance, but this role specifically pertains to our
Technology Delivery Center (TDC).
Established in Barcelona in ****, the TDC operates as an integral part of Zurich Insurance Group, providing cutting-edge technological solutions and support to Zurich's local and general business units.
In essence, Zurich TDC is where technology meets the vast reach of a multinational company. We specialize in areas such as software development, data analytics, cybersecurity, and IT infrastructure. Our primary mission is to support Zurich's strategic goals and enhance operational efficiency through innovative technology solutions.
If you're considering a role with us, know that you'll be joining a hub of technological excellence dedicated to driving Zurich's success on a global scale.
What Can You Expect?
And you might be thinking: This is great, what will my day-to-day be like, at TDC? I'm glad you asked.




As a Senior AI Engineer – Agentic Workflows you will have the opportunity to:
Design Agentic Workflows & Problem Decomposition:
Architect end-to-end workflows using LangGraph (or similar), breaking complex problems into composable steps, states, and policies. Translate high-level business problems into structured agentic solutions, defining workflows, components, and trade-offs across multiple design options.
Build Skills, Tools, and Agents:
Implement reusable skills, tools, and agents, and compose them into workflows that are maintainable and testable. Demonstrate strong judgement on when to build a skill vs. a tool vs. an agent vs. a workflow, based on problem decomposition, system design trade-offs, and long-term maintainability—balancing accuracy, complexity, observability, and long-term reuse.
Model Strategy, Integration & Performance Optimization:
Integrate and operate multiple LLM providers, optimising for latency, cost, and output quality. Optimize prompt engineering, token usage, chunking strategies, and inference efficiency across the platform. Design typed schemas (e.g., Pydantic models) for reliable data flows, tool contracts, and structured outputs.
Evaluations, Quality & Observability:
Define and implement evaluation strategies (offline and online),



datasets, metrics, and guardrails to validate agent behaviour and measure regression over time. Implement logging, tracing, and monitoring for agentic systems using tools like Langfuse or LangSmith.
Cross-functional Collaboration:
Partner with data scientists, engineers, and product teams to translate requirements into robust agentic capabilities and deliver measurable value. Support colleagues and junior engineers through mentorship, code review, and technical guidance. Guide the team in building robust evaluation practices and establishing strong quality standards. Use AI assistants (including Claude Code) in day-to-day work for prototyping, refactoring, testing, and documentation—while applying strong engineering judgement
.
What Makes You a great Fit?
While we're not seeking perfection or expecting you to save the world, we believe that if you meet some of these requirements, you'll be a fantastic fit for our team.
We are waiting for you
5+ years Python development with strong software engineering fundamentals
Hands-on experience building production systems with Large Language Models
High ownership & proactive communication: Delivers assigned outcomes autonomously, keeping progress visible and proactively surfacing blockers, changes in approach, and trade-offs
Proven experience with LangGraph or similar agentic frameworks (LangChain, other orchestration frameworks acceptable)
Strong understanding of evaluation methodologies for LLM/agent quality (datasets, metrics, human review, regression testing <

📌 Senior Ai Engineer (Laza)
🏢 Livewell
📍 Laza