Lead Solutions Architect - Generative AI (EMEA Emerging DNB)

Lead Solutions Architect, Generative AI

Databricks is the data and AI platform trusted by over 20,000 organizations globally, including 70% of the Fortune 500. The company provides a unified lakehouse platform that combines data warehousing and machine learning capabilities, enabling customers to build, deploy, and scale data and AI applications at enterprise scale. Databricks operates across 30+ offices worldwide and continues to expand its influence in how organizations approach generative AI and large language models.

This role sits within Databricks' Field Engineering team, specifically supporting the EMEA Emerging Digital Natives and Startups business unit. You will serve as the principal technical authority on generative AI for one of the company's highest-growth and most technically demanding regions, partnering closely with Account Teams to translate ambitious GenAI concepts into production systems for fast-scaling, cloud-native customers.

What you'll do

• Be the go-to technical expert on generative AI, large language models, and applied machine learning for EMEA's digital-native accounts, leading the most complex and strategic customer engagements across the region.

• Partner with Solutions Architects, Solutions Engineers, and Account Teams to design, scope, and de-risk GenAI use cases including retrieval-augmented generation, agentic systems, fine-tuning, and evaluation frameworks.

• Build hands-on proofs of concept and reference implementations that operationalize large-scale LLM and deep learning workloads on Databricks' stack (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog), aligned with the rapid iteration pace these customers demand.

• Lead fine-tuning engagements on open-source models such as Llama-family architectures, including judge-based and label-efficient evaluation approaches for domains where quality and safety matter most.

• Serve as a bridge between field teams and Product Engineering, channeling customer feedback into roadmap decisions and communicating product direction back to the field.

• Enable the broader EMEA Field Engineering team through workshops, reference architectures, and internal training, scaling GenAI expertise across approximately 70 Solutions Architects and Solutions Engineers.

• Represent Databricks externally as a technical leader through conference presentations, published content, and customer executive briefings.

What you'll bring

• Deep understanding of the LLM landscape across proprietary and open-source models, with ability to articulate informed perspectives on their capabilities, trade-offs, and fit for specific use cases.

• Expert knowledge of the modern GenAI stack: LLM application patterns, fine-tuning and model customization, prompt engineering, evaluation techniques, and safety guardrails.

• Strong foundations in machine learning and deep learning, including distributed training, GPU workloads, and the complete MLOps lifecycle from experiment tracking through monitoring and serving.

• Proficiency in Python and the ML ecosystem (PyTorch, Transformers, MLflow, Spark), with ability to build production-quality reference implementations.

• Hands-on experience with the Databricks platform (Mosaic AI, Model Serving, Vector Search, Unity Catalog) and cloud platforms including AWS, Azure, or GCP.

• Excellent consultative and communication skills—able to build trust with both hands-on engineers and senior technical executives while explaining complex GenAI trade-offs clearly.

• Proven track record in technical leadership and mentorship that elevates the capability of colleagues around you.

• Based in the United Kingdom, able to work across EMEA time zones, and willing to travel to customer sites within the region as needed.

Nice to have

• Public technical presence through conference speaking, published research, blogs, or open-source contributions in the ML or GenAI space.

• Domain expertise in regulated or high-stakes industries such as healthcare, life sciences, or financial services where model quality and safety evaluation are critical.

• Experience working with Product and Engineering teams to shape technical roadmaps.