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the recruiter for this position. Nice to meet you!

• First, a little bit about what I like the most about working at: The environment here is incredibly collaborative and innovative. Our tech-driven mindset fosters continuous learning and growth, creating an atmosphere where everyone can thrive
• Let me introduce us. You’re reading about , a global leader in insurance, but this role specifically pertains to our Established in Barcelona in 2006, the TDC operates as an integral part of Zurich Insurance Group, providing cutting-edge technological solutions and support to Zurich's local and global 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

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
• 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
• 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
• 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
• Proven ability to decompose complex, ambiguous business problems into scalable technical solutions, from high-level requirements to detailed design
• Experience with agent-building frameworks and tools (e.g., AutoGen, Deep Agents)
• Comfort using AI assistants (e.g., Claude Code) as part of the daily engineering workflow
• Familiarity with LLM observability tools (Langfuse, LangSmith, etc.)
• Background with vector databases and RAG patterns
• Experience with knowledge graphs and semantic data structures
• Understanding of cost optimisation and token accounting in LLM systems
• Production experience with async Python patterns (asyncio, concurrent request handling)
• Experience with Azure deployment and cloud-native architectures
• Knowledge of evaluation frameworks and metrics for AI output quality

As well as a and a , we offer:

• competitive salary
• yearly bonus
• To support your work-life balance, we have adopted a flexible working model
• Option to work abroad up to 25 days yearly
• Over 300 euros to set up your home office and additional monthly home office allowance
• Wide range of internal and external trainings, including English, German and Spanish classes depending on

needs

• Ticket restaurant and Health Insurance with the flexibility to exchange it for other benefits
• Special banking and insurance conditions plus Exclusive Employees
• Functional diversity benefits
• Stock options and mortgage benefits