Senior Specialist Solutions Architect (AI/ML)

About the role

Databricks is looking for a Senior Specialist Solutions Architect (ML & AI) in London. You will act as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization, partnering with Solution Architects to help enterprise and strategic customers design production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also deepen your expertise in GenAI, ML, MLOps and LLMOps, mentor colleagues and become an AI thought leader.

Key responsibilities

• Design and implement production-level ML and AI workloads, including end-to-end pipelines, training and inference optimization, MLOps lifecycle management and integration with cloud-native services.
• Act as a practitioner for enterprise GenAI solutions, covering RAG architectures, agentic systems (tool-calling, multi-agent orchestration, guardrails), AI observability and natural language querying of structured data.
• Support Solution Architects during the technical sales cycle by building MVPs, running deep-dive sessions and aligning AI solutions with complex customer needs.
• Work with product and engineering teams to represent the customer voice, define priorities and influence the platform's AI roadmap.
• Grow the community and drive platform adoption through tutorials, training materials, conference presentations and hackathons.

Required profile

• 10+ years of hands-on industry data science and machine learning experience, focused on either ML engineering (production cloud infrastructure on AWS/Azure/GCP, model monitoring) or data science/AI (LLMs, agentic systems, vector databases, fine-tuning, HuggingFace, LangChain).
• Hands-on experience with distributed Spark-based systems and data engineering concepts; Apache Spark preferred.
• Pre-sales or post-sales experience with external clients across industries; 5+ years of customer-facing experience preferred.
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
• Able to learn the technical training and role expectations within 3 months of hire and to travel up to 30% when needed.
• Proven ability to explain complex technical concepts to technical and non-technical audiences.