Senior Specialist Solutions Architect (Ai/Ml)

Databricks Inc.; Greater London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Job summary

Databricks Inc. is seeking a Senior Specialist Solutions Architect (ML & AI) to serve as the trusted ML/AI expert for customers and Field Engineering, guiding enterprise deployments on the Databricks Data Intelligence Platform.

You will mentor colleagues, advance GenAI initiatives, and contribute to AI thought leadership through tutorials, training, and industry conference presence.

Qualifications

• 10+ years of hands-on industry DS/ML experience with a focus on ML Engineering or Data Science/AI.
• Experience with distributed Spark based systems.
• Experience with data engineering concepts.
• Pre-sales or post-sales experience working with external clients; 5+ years of customer-facing experience preferred.
• Willingness to travel up to 30%.

Responsibilities

• Architect production-level ML/AI workloads, including end-to-end pipelines and MLOps lifecycle management.
• Lead GenAI initiatives, including RAG architectures, agentic systems, AI observability, and NLP querying of data.
• Provide advanced technical support to Solution Architects during the technical sales cycle, build MVPs, and run deep-dive sessions.
• Collaborate with product and engineering to reflect customer voice and influence the AI roadmap.
• Create tutorials and training materials; contribute to AI thought leadership and community growth.

Skills

Data Science

Machine Learning

AI

LLM

GenAI

Education

Graduate degree in a quantitative discipline

Tools

Apache Spark

HuggingFace

Langchain

Job description

ReqID:FEQ327R501

Location: London

Skills: Data Science, Machine Learning, AI, LLM, GenAI

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.
• Provide advanced technical support to Solution Architects during the technical sales cycle by building MVPs, leading deep-dive sessions, and aligning AI solutions with complex customer business challenges.
• 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
• [ 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