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AI Engineer - FDE (Forward Deployed Engineer)Databricks · Remote - United Kingdom
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Databricks

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AI Engineer - FDE (Forward Deployed Engineer)

✓ This company has sponsored visas before. The posting doesn't say so, but it's still worth applying.

🗓️ Posted 2026-08-18 Remote - United Kingdom Hybrid ICT
💰 Salary Not shared 📊 Market 8,333 GBP–15,000 GBP/mo

About the Company

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. The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team that delivers professional services engagements to help customers build and productionize first-of-its-kind AI applications. The team works cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams.

Responsibilities

  • ● Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems
  • ● Own production rollouts of consumer and internally facing GenAI applications
  • ● Serve as a trusted technical advisor to customers across a variety of domains
  • ● Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
  • ● Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

Requirements

  • ● Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
  • ● Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
  • ● Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
  • ● Experience building production-grade machine learning deployments on AWS, Azure, or GCP
  • ● Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
  • ● Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
  • ● Passion for collaboration, life-long learning, and driving business value through AI
  • ● Experience using the Databricks Intelligence Platform and Apache Spark to process large-scale distributed datasets (Preferred)
  • ● Willing to travel once every 4-8 weeks to see customers (as needed)