Forward Deployed Engineer

Databricks · London, United Kingdom · Professional Services Operations · listed October 8, 2026

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The shape of it

Seniority

Not stated

Where

Not stated

Requirements listed

Length

688 words

In the posting’s own words

The Forward Deployed Engineering (FDE) team is a highly specialized, customer-facing software engineering team at Databricks. We work with Databricks most strategic customers to design, build, and productionize first-of-their-kind data and AI solutions. This team is the right fit for you if you love working side-by-side with customers, collaborating with teammates, and pushing your curiosity across the latest trends in data, applications, and AI innovation.

What it asks for · 7

Engineering Depth: Strong background in software engineering with experience across backend, frontend, and systems integration. Proficiency in Python, SQL, Java/Scala, JavaScript/TypeScript, and modern frameworks.
Application Delivery: Demonstrated ability to design, build, and deploy production applications that combine data pipelines, ML/AI models, and user-facing interfaces.
AI/ML Experience: Familiarity working with AI APIs such as OpenAI, Anthropic, and Gemini into applications, and leveraging AI code generation tools to accelerate productivity.
Customer Impact: Proven track record of delivering technical solutions in enterprise environments that drive measurable outcomes.
Collaboration & Communication: Ability to engage across a broad stakeholder range, from engineers to C-level executives, translating complex concepts into actionable solutions.
Learning Mindset: Curiosity, adaptability, and eagerness to explore new technologies, domains, and customer challenges.
Ability and interest to travel up to 50% as needed to client sites.

What the job covers

Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
Application Engineering: Design and develop applications spanning backend, frontend, and integrations, bringing data and AI to life for enterprise users leveraging the Databricks platform.
Solution Delivery: Deliver production-grade systems from data ingestion and transformation through ML/AI model integration to user-facing applications and enablement.
Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
Cross-Functional Collaboration: Partner with Sales, Product, and Field Engineering to ensure a seamless customer journey from pre-sales through post-deployment.
Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Tools and skills named

Data

Databricks6×
Data pipelines

Languages

Java
JavaScript
Python
Scala
SQL
TypeScript

Models & research

Machine learning3×

Product & design

Roadmap

Ways of working

Cross-functional

Words the posting leans on

customer9×
engineering8×
data7×
applications6×
design6×
solutions6×
impact5×
software4×
curiosity3×
deliver3×
engineers3×
integration3×
systems3×
adaptability2×
architecture lead2×
backend frontend2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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