Senior AI Engineer (Databricks) - UK

About this role

At DATAPAO, data ignites passion, community fuels collaboration, and growth knows no bounds. We are a leading Data Engineering and AI consulting company backed by Databricks and recognized for our unmatched delivery standards and rapid growth. We have been named Databricks EMEA Emerging Business Partner of the Year (2024), achieved the Golden Tier status in the Databricks Partner Program , and made three consecutive appearances on the Financial Times FT1000 list .

We are currently looking for a Senior AI Engineer to join us remotely in the UK. This will be our first AI hire in the UK. What (exactly) will you do? As our first AI Engineer in the UK, you’ll lead engagements to help our customers build and productionize tailored AI applications in the Databricks platform , using the latest technologies to deliver business impact for our top clients. You’ll own the technical delivery of AI solutions, whether you’re working solo as an AI Engineer or heading up a delivery team.

Your responsibilities will span across the following dimensions: Project Planning & Delivery Technical Architecture: Lead the technical scoping, design high-level architectures, and define the roadmap for AI and Generative AI solutions. Execution & Leadership: Take ownership - either delivering the project independently or acting as the Delivery Technical Lead for a small team of engineers. Customer Interface: Serve as the primary technical contact for our customers, ensuring the systems you build solve their specific business challenges.

Strategic Advisory: Between active project cycles, act as a senior technical advisor for our EMEA customers and Databricks partners to navigate complex Generative AI and traditional Machine Learning challenges. AI & Platform Consultancy Production-Grade Solutions: Build robust and scalable solution architectures that leverage the latest technologies Enablement: Lead technical workshops to empower client teams, ensuring they have the expertise to manage and scale the AI platforms you help them deploy.

What does it take to fit the bill? Technical Expertise You have 5+ years of experience in AI or Machine Learning Engineering with a focus on cloud platforms (preferably Azure or AWS, but GCP is also ok); You are proficient in MLOps using MLflow - taking models from local environments to fully automated, monitored production pipelines; You have experience building production systems in Databricks or in a comparable enterprise cloud environment, utilizing PySpark, SQL, Delta Lake, Unity Catalog (or similar enterprise governance), and Databricks AI features; You have a good understanding of Large Language Models (LLMs) and experience implementing them using modern frameworks and libraries (e.g., LangGraph, Provider-specific agentic frameworks, like Claude Agents SDK) You have strong Python knowledge of the most common Data Science and ML libraries You have good knowledge of data visualization tools/libraries [BONUS]: Proficiency in deep learning frameworks (PyTorch/TensorFlow) or distributed computing (Spark).