Sr. Specialist Solutions Architect

About the role

<p data-pm-slice="1 1 []">FEQ228R125</p> <p>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 <strong>governed, cost-efficient agents and ML systems running on the Databricks Data Intelligence Platform</strong>.</p> <p>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.</p> <p>This role reports to the Manager, Specialist Solutions Architects – Switzerland, Austria &amp; Eastern Europe.</p> <h3><strong>The impact you will have</strong></h3> <ul> <li><strong>Win the technical decision for AI on Databricks.</strong> Lead discovery, architecture design, demos, proofs of concept and MVPs for agent, GenAI and ML use cases in competitive evaluations.</li> <li><strong>Design production-grade agent systems.</strong> 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</li> <li><strong>Make agent quality measurable.</strong> 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.</li> <li><strong>Govern AI at enterprise scale.</strong> Position the AI Gateway as the central control point for model access, guardrails, PII protection, usage tracking and rate limiting.</li> <li><strong>Scale your expertise.</strong> Enable SAs and partners with workshops, reusable assets and reference architectures.&nbsp;</li> <li><strong>Influence the product.</strong> Bring structured customer feedback and requirements specific to the market to Product Management and Engineering.</li> <li><strong>Be a visible voice.</strong> Represent Databricks at customer executive briefings, meetups, conferences and in written content.</li> </ul> <h3><strong>What we look for</strong></h3> <ul> <li>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).</li> <li><strong>A track record of shipping LLM and agent systems to production</strong>, not just prototypes, including evaluation, monitoring and cost management.</li> <li>Deep knowledge of agent architecture: tool use and function calling, MCP, agent memory and state, orchestrating multiple agents, and retrieval and context design.</li> <li>Strong practical experience <strong>evaluating GenAI systems</strong>: tracing, LLM-as-a-judge, building evaluation datasets, regression testing and observability in production.</li> <li>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.</li> <li>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.</li> <li>Strong grounding in classical ML and MLOps: model development, deployment, monitoring and lifecycle management at scale.</li> <li>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.</li> <li>Experience with at least one major cloud platform (AWS, Azure or GCP) and modern data platforms.</li> <li>Proven ability to influence technical leaders up to CTO/CDO level and to explain complex AI topics in business

Skills