AI Engineer - Agentic Workflows

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AI Engineer – Agentic Workflows

We're seeking an AI Engineer – Agentic Workflows to design, implement, and own generative AI systems in production.

You will independently lead technical initiatives, architect agentic workflows, and drive reliability improvements across multi-step LLM systems. Working with LangGraph (or similar frameworks) and leading LLM providers, you'll translate complex business problems into scalable, production-ready solutions.

A core part of this role is establishing evaluation practices, observability standards, and cost optimization strategies while mentoring junior engineers and contributing to team technical direction.

Your role

As AI Engineer, your main responsibilities will involve: 

• Design & Own Workflows: Build end-to-end agentic workflows (e.g., LangGraph), balancing complexity, performance, and maintainability.
• Problem Solving: Translate ambiguous business needs into structured technical solutions and architectures.
• Reusable Components: Develop production-grade agents, tools, and skills with clear interfaces, tests, and documentation.
• Architecture Decisions: Select frameworks and design patterns based on use cases and constraints.
• Model Integration: Manage multi-LLM integrations, optimizing for latency, cost, and quality.
• Evaluation & Quality: Define metrics, datasets, and guardrails to ensure reliability and prevent regressions.
• Data Architecture: Design schemas and validation layers for reliable, structured data flows.
• Observability & Support: Implement logging, monitoring, and incident response practices.
• AI-Driven Dev: Use AI tools to accelerate development while maintaining code quality.
• Cross-functional Leadership: Align with product, data, and engineering teams to deliver solutions.
• Mentorship: Support and guide junior engineers on best practices.

Zamestnanecké výhody, benefity:

Compensation for roles at Zurich depends on a wide array of factors including but not limited to the specific role, skill set, level of experience, and subject to applicable law. Zurich thus provides a range of compensation aligned to internal job architecture and market benchmarks to ensure fair and consistent pay for comparable roles.

The starting base salary range for this position is 2930 Eur.

Working time benefits

Personal days off, Concentrated work week, Additional vacation, Home office, Extra days off at occasion of childbirth, Sabbatical leave, Workation

Monetary benefits

Life insurance from Zurich Austria, Compensation for salary loss during sick leave, 3rd pension pillar contribution, Risk Life Insurance, Meal contribution on top of the legally required minimum, Years of service bonus, Wedding bonus, Baby bonus

Other benefits

Electronic cafeteria, Maternity leave benefits, Massages in the office

Learning/Development

Professional Certifications, Online Education Portals, Extensive Onboarding program, Strengths based culture (GALLUP)

• Location: Bratislava
• Schedule: full-time
• Form: hybrid - occasional home office possible

About us

At our company, we recognize the importance of fostering an open-minded, safe and inclusive environment for everyone. We stand with diversity and respect different backgrounds and lifestyles. That's why we've implemented numerous initiatives to ensure our employees feel comfortable, accepted, and respected at all times.

Požiadavky na zamestnanca:

As AI Engineer, your skills and experience will ideally include:

• 2-4 years of professional software engineering, data science, or AI engineering experience
• At least 2 years of hands-on experience building production generative AI systems
• Strong Python expertise with demonstrated software engineering fundamentals (testing, CI/CD, code review)
• Production experience with LLM-based systems, including advanced prompting techniques, API integration, and workflow orchestration
• Proven experience with LangGraph or similar agentic frameworks (LangChain, CrewAI, AutoGen, or custom orchestration)
• Solid understanding of evaluation methodologies and quality metrics for LLM/agent systems
• Experience independently leading technical initiatives from design through production deployment
• Track record of making architectural decisions and understanding their trade-offs

  Nice to Have

• Active user of AI assistants (e.g., Claude Code, Cursor, Copilot) with demonstrated productivity gains
• Experience with LLM observability platforms (Langfuse, LangSmith, Weights & Biases, Arize)
• Production experience with vector databases (Pinecone, Weaviate, Qdrant) and RAG architectures
• Demonstrated experience optimizing LLM costs and implementing token management strategies
• Strong understanding of async Python patterns and concurrent request handling in production
• Experience deploying and operating AI systems on Azure (or AWS/GCP) with cloud-native architectures
• Experience designing evaluation frameworks and establishing quality benchmarks for AI systems
• Familiarity with fine-tuning, prompt optimization, or model selection strategies

 Growth & Development

• Lead increasingly complex initiatives and own critical system components
• Shape technical direction and contribute to team standards and best practices
• Expand influence across engineering, data science, and product organizations
• Develop expertise in emerging agentic AI patterns and evaluation methodologies
• Opportunity to grow toward senior or staff engineer roles