Databricks

Builds cloud software for data analysis and AI

Senior Specialist Solutions Architect - AI/ML

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours

Full-timeLondon, UKNo salary listed

About the Job

Requirements

At least 10 years of hands-on industry data science or machine learning experience, focused on either ML engineering or data science/AI.
For ML engineering: experience building and maintaining production-grade cloud infrastructure on AWS, Azure, or GCP to support deployment of ML applications and monitoring model performance.
For data science/AI: experience applying advanced techniques in large language models, agentic systems, vector databases, fine-tuning, and deployment tools such as Hugging Face and LangChain.
Hands-on experience with distributed Spark-based systems.
Experience with data engineering concepts or a good understanding of them.
Pre-sales or post-sales experience working with external clients across a variety of industry markets.
A graduate degree in a quantitative discipline, such as Computer Science, Engineering, Statistics, or Operations Research, or equivalent practical experience.
Ability to meet expectations for technical training and role-specific outcomes within three months of hire.
Ability to travel up to 30% when needed.

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.
Serve as a practitioner for enterprise generative AI solutions, specializing in retrieval-augmented generation 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 minimum viable products, leading deep-dive sessions, and aligning AI solutions with complex customer business challenges.
Collaborate cross-functionally with product and engineering teams to represent the voice of the customer, define priorities, and influence the platform's AI roadmap.
Drive community growth and AI platform adoption by creating technical tutorials and training materials, presenting at industry conferences, and leading hackathons.
Mentor colleagues and establish expertise as an AI thought leader.

Desired Qualifications

At least five years of customer-facing experience is preferred.
Experience working with Apache Spark to process large-scale distributed datasets is preferred.
Ability to communicate and teach complex technical concepts to technical and non-technical audiences.

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

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

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 and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size: 10,001+
Company stage: Late Stage VC
Total funding: $32.1B
Headquarters: San Francisco, CA
Founded: 2013

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