Sr. Specialist Solutions Architect

As a Senior Specialist Solutions Architect (Sr. SSA) for AI/ML, you will be the go-to technical expert for Databricks' AI platform across our customers. You will help them move from AI experiments to governed, cost-efficient agents and ML systems running on the Databricks Data Intelligence Platform .

You will work with Account Executives and Solutions Architects to win strategic opportunities. You will design architectures for advanced agent and ML use cases and lead hands-on proofs of concept and MVPs. You will act as a trusted advisor to customer technical leaders on AI strategy, governance and economics. You will also shape our AI go-to-market in the region, enable the wider field team, and feed what you learn from customers back to Product and Engineering.

This role reports to the Manager, Specialist Solutions Architects – Switzerland, Austria & Eastern Europe.

The impact you will have

• Win the technical decision for AI on Databricks. Lead discovery, architecture design, demos, proofs of concept and MVPs for agent, GenAI and ML use cases in competitive evaluations.
• Design production-grade agent systems. Architect agents and multi-agent applications using Agent Bricks, Databricks Apps, MCP tools, Lakebase, AI Search and the Foundation Model APIs. Govern assets under Unity Catalog
• Make agent quality measurable. Help customers build evaluation and observability into everything they ship, using MLflow tracing, domain-specific LLM judges, labelled evaluation datasets, release gates and production monitoring.
• Govern AI at enterprise scale. Position the AI Gateway as the central control point for model access, guardrails, PII protection, usage tracking and rate limiting.
• Scale your expertise. Enable SAs and partners with workshops, reusable assets and reference architectures.
• Influence the product. Bring structured customer feedback and requirements specific to the market to Product Management and Engineering.
• Be a visible voice. Represent Databricks at customer executive briefings, meetups, conferences and in written content.

What we look for

• 7+ years of hands-on experience in machine learning, AI engineering or data science, including customer-facing technical work (pre-sales, consulting or technical leadership).
• A track record of shipping LLM and agent systems to production , not just prototypes, including evaluation, monitoring and cost management.
• Deep knowledge of agent architecture: tool use and function calling, MCP, agent memory and state, orchestrating multiple agents, and retrieval and context design.
• Strong practical experience evaluating GenAI systems : tracing, LLM-as-a-judge, building evaluation datasets, regression testing and observability in production.
• Hands-on with at least one modern agent framework (e.g. LangGraph, OpenAI Agents SDK, Google ADK, DSPy). You should be framework-agnostic in how you design.
• Solid understanding of the foundation-model landscape (e.g. Anthropic, OpenAI, Google, open-weight models) and the trade-offs between quality, latency, cost and data residency.
• Strong grounding in classical ML and MLOps: model development, deployment, monitoring and lifecycle management at scale.
• Strong software engineering skills in Python and SQL. You use AI coding assistants (e.g. Claude Code, Cursor) daily and can build a working demo application quickly.
• Experience with at least one major cloud platform (AWS, Azure or GCP) and modern data platforms.
• Proven ability to influence technical leaders up to CTO/CDO level and to explain complex AI topics in business terms.
• Communication: Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences.