Senior EMEA AI Solutions Architect
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will provide technical leadership to strategic customers on big data and AI projects, from architecture to model deployment. You will partner with GTM leadership and account teams, build credibility with CAIOs, CDOs and CTOs, run workshops and POCs, design agentic AI use cases on Databricks, implement evaluation and monitoring with MLflow, and act as a tier-3 escalation point.
Requirements
- 10+ years in customer-facing, pre-sales or consulting roles influencing technical executives
- Experience with production-grade ML and generative AI applications
- Hands-on experience building agentic AI solutions including RAG, tool calling and multi-agent orchestration
- Understanding of agentic AI evaluation methodologies
- Familiarity with frontier models from Anthropic, OpenAI and Google Gemini
- Proficiency in SQL, Python, Apache Spark, cloud platforms and Lakehouse architectures
- Experience collaborating with GSIs and consulting organizations
- Hands-on experience with AWS, Azure or GCP
- Undergraduate degree or higher in a technical field
Responsibilities
- Provide technical leadership guiding customers to successful big data implementations
- Design and execute engagement strategies and sales plays to drive AI adoption
- Act as trusted advisor to CAIOs, CDOs and CTOs
- Run workshops, POCs and build customer-facing collateral
- Lead design and implementation of agentic AI use cases using Databricks Agent Framework and Agent Bricks
- Implement evaluation and monitoring using MLflow, LLM judges and tracing
- Translate field insights into product roadmap recommendations
- Act as tier-3 escalation point for complex technical challenges
- Refine the sales qualification and POC intake process