Lead Solutions Architect - Generative AI (EMEA Emerging DNB)
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 be the deep technical authority on Generative AI and LLMs for the EMEA Emerging Digital Natives business unit. You will scope and de-risk GenAI use cases, build proofs of concept on Databricks, lead fine-tuning engagements, bridge to Product and Engineering, mentor colleagues, and represent Databricks externally. Travel across Europe is required.
Requirements
- Strong understanding of the LLM landscape
- Expertise in the GenAI stack: RAG, agents, fine-tuning, evaluation, guardrails
- Foundations in machine learning, deep learning, distributed training, GPU workloads, MLOps
- Proficiency in Python, PyTorch/Transformers, MLflow, Spark
- Experience with Databricks or ability to ramp quickly; cloud experience on AWS, Azure, or GCP
- Excellent communication and consultative skills
- Technical leadership and mentorship
- Based in the United Kingdom and able to work across EMEA time zones
- Willingness to travel to customer sites
Responsibilities
- Serve as technical authority on Generative AI, LLMs, and applied ML
- Scope, design, and de-risk GenAI use cases with account teams
- Build proofs of concept and reference implementations on Databricks
- Lead fine-tuning and model-customisation engagements on open LLMs
- Channel field feedback to Product and Engineering
- Enable and mentor Field Engineering through workshops and reference architectures
- Represent Databricks externally through talks, blogs, and executive briefings