Senior Specialist Solutions Architect - AI/ML

About the role

Databricks is looking for a Senior Specialist Solutions Architect (Sr. SSA) for AI/ML in Zurich. As the go-to technical expert for its AI platform, you will help customers move from AI experiments to governed, cost-efficient agents and ML systems. You report to the Manager, Specialist Solutions Architects – Switzerland, Austria & Eastern Europe.

Key responsibilities

• Work with Account Executives and Solutions Architects to win strategic opportunities and lead discovery, demos, proofs of concept and MVPs for agent, GenAI and ML use cases.
• Design production-grade agent systems using Agent Bricks, Databricks Apps, MCP tools, Lakebase, AI Search and Foundation Model APIs, and govern assets under Unity Catalog.
• Help customers build evaluation and observability using MLflow tracing, LLM-as-a-judge, labelled evaluation datasets, release gates and production monitoring.
• Position the AI Gateway as the central control point for model access, guardrails, PII protection, usage tracking and rate limiting.
• Enable SAs and partners through workshops, reusable assets and reference architectures, and bring customer feedback to Product and Engineering.
• Represent Databricks at customer briefings, meetups and conferences, and contribute to written content.

Required profile

• 7+ years of hands-on experience in machine learning, AI engineering or data science, including customer-facing technical work.
• Track record of shipping LLM and agent systems to production, including evaluation, monitoring and cost management.
• Ability to influence technical leaders up to CTO/CDO level and explain complex AI topics in business terms.
• Proven ability to teach complex technical concepts to technical and non-technical audiences.

Required skills

• Deep knowledge of agent architecture: tool use, function calling, MCP, agent memory and state, orchestration and retrieval design.
• Experience evaluating GenAI systems: tracing, LLM-as-a-judge, evaluation datasets, regression testing and observability.
• Hands-on with at least one modern agent framework (e.g. LangGraph, OpenAI Agents SDK, Google ADK, DSPy).
• Solid understanding of foundation models and their trade-offs, and strong classical ML and MLOps.
• Python and SQL, with daily use of AI coding assistants.
• Experience with at least one major cloud platform (AWS, Azure or GCP) and modern data platforms.