Senior Specialist Solutions Architect (AI/ML)

Databricks; Greater London; On-site; GBP 120,000 - 170,000; Full time

Job summary

Databricks is seeking a Senior Specialist Solutions Architect (ML & AI) to act as the trusted technical ML and AI expert for customers and Field Engineering. You will partner with Solution Architects to guide enterprise clients in architecting production‑grade ML/AI applications on the Databricks platform.

You will advance GenAI, MLOps, and LLMOps, mentor colleagues, and influence the product roadmap while delivering practical tutorials, training, and thought leadership at conferences and

Qualifications

• 10+ years hands-on DS/ML experience, focus on production ML/AI workloads.
• Experience with distributed Spark based systems.
• Strong data engineering concepts knowledge.
• Pre-sales or post-sales client engagement experience.
• Excellent communication to both technical and non-technical audiences.

Responsibilities

• Architect production-grade ML/AI workloads and end-to-end pipelines on Databricks platform.
• Lead GenAI initiatives, agentic systems, observability, and tool-calling patterns.
• Influence product roadmap through voice of the customer and cross-functional collaboration.
• Create tutorials and training, contribute to industry conferences and hackathons.

Skills

DS/ML experience

Distributed Spark

Data engineering concepts

Pre/post-sales experience

Customer-facing

Communication

Education

Graduate degree in quantitative discipline

Tools

HuggingFace

Langchain

Vector databases

Job description

Mission

As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers in architecting production‑grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting‑edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader.

Impact you will have

• Architecting Workloads: Design and implement production‑level ML and AI workloads, including end‑to‑end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud‑native services.
• GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool‑calling, multi‑agent orchestration, and guardrails), AI observability, and natural language querying of structured data.
• Product Influence: Collaborate cross‑functionally with product and engineering teams to represent the voice of the customer, define priorities, and influence the platform’s AI roadmap.
• Thought Leadership: Drive community growth and AI platform adoption through the creation of technical tutorials and training materials, as well as by presenting at industry conferences and leading hackathons.

What we look for

• Experience: 10+ years of hands‑on industry DS/ML experience, with a focus on either:
  • ML Engineering: Building/maintaining production‑grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance.
  • Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine‑tuning, and deployment tools (e.g., HuggingFace, Langchain).
• Hands‑on experience working with Distributed Spark based systems.
• Experience with data engineering concepts or a good understanding of data engineering concepts.
• Pre‑sales or post‑sales experience working with external clients across a variety of industry markets.
• Minimum of 5+ years of customer‑facing experience would be preferred.
• Experience working with Apache Spark™ to process large‑scale distributed datasets.
• Communication: Proven ability to communicate and teach complex technical concepts to both technical and non‑technical audiences.
• Core Traits: Passion for lifelong learning, collaboration, and driving business value through AI.
• Education: Graduate degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research, etc) or equivalent practical experience.
• Can meet expectations for technical training and role‑specific outcomes within 3 months of hire.
• Can travel up to 30% when needed.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical or mental ability, political affiliation, race, religion, sexual orientation, socio‑economic status, veteran status, and other protected characteristics.