Senior Specialist Solutions Engineer (AI/ML)
Application analysis
Senior Specialist Solutions Engineer (AI/ML) at Databricks is a forward deployed data & ai platform role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Solutions / Sales Engineering role centers on technical discovery, demos, POCs, and helping buyers build internal consensus. Key signals from the listing: AWS, Azure, GCP, Government / DoD context.
About Databricks
Databricks sells a unified data platform to enterprises. Forward deployed engineers help customers migrate workloads and prove value on live data. The role is anchored in London, United Kingdom, so expect on-site customer work in that region.
Signals in the listing
Stand out for Senior Specialist Solutions Engineer (AI/ML)
- Lead your application with one paragraph tying Senior Specialist Solutions Engineer (AI/ML) to a specific customer or deployment you owned — Databricks hires for shipped outcomes, not tool lists.
- Bring a tight demo narrative: customer pain, live workflow, and measurable before/after — treat the interview like a compressed POC.
- Show how you qualify opportunities and say no to bad-fit pilots; Databricks values technical judgment in customer-facing roles.
- State clearance status clearly up front (active, expired, or eligible) and mention any prior NIPR/SIPR, IL5, or government cloud accreditation work — recruiters filter on this early.
- This role is tied to London, United Kingdom — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at Databricks
- Demonstrate Spark/SQL fluency with a concrete example — Databricks will probe for specifics, not buzzwords.
- Demonstrate enterprise stakeholder management with a concrete example — Databricks will probe for specifics, not buzzwords.
- Strong candidates show they can whiteboard a lakehouse migration and then actually implement the first milestone.
- Read recent engineering blog posts, product launches, and customer stories on databricks.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
ReqID: FEQ327R256
Recruiter: Dina Hussain
Location: London
Skills: Data Science, Machine Learning, AI, LLM, GenAI
As a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as an ML expert. You will be reporting to the Manager, Field Engineering (Specialist Team)
The impact you will have:
Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services. Provide advanced technical support to the Solution Architects during the technical sales cycle by building MVPs, leading deep-dive technical sessions, and strategically aligning ML/data science solutions to complex customer business challenges using relevant real-world examples. Serve as the trusted technical advisor for customers developing GenAI solutions, specializing in the design and implementation of RAG architectures on enterprise knowledge bases, enabling natural language querying of structured data, and establishing content generation and monitoring frameworks. Drive community growth and platform adoption through thought leadership activities, including the creation of technical tutorials and training materials, as well as leading hackathons and presenting at industry conferences.
What we look for:
Experienced, technical, customer-facing, and with a background in Data Science / Machine Learning, and Data Engineering. Looking to learn and develop in a customer-facing technical role as a subject matter expert (SME) in a pre-sales environment. Pre-sales or post-sales experience working with external clients across a variety of industry markets
Data Science/ML Skills
Hands-on industry ML experience in at least one of the following:
ML Engineer: Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring Data Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI Hands-on experience working with Distributed Spark based systems. Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and teaching technical concepts to non-technical and technical audiences alike Passion for collaboration, life-long learning, and driving our values through ML [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets 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 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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.