Lead Forward Deployed Engineer, Databricks 2026- US, UK

Aimpoint Digital is a market-leading data, AI, and operations research advisory and solution engineering firm. We help organizations build modern data platforms, enterprise AI systems, decision intelligence solutions, optimization models, and production analytics capabilities.

We are one of the strongest technical partners in the Databricks ecosystem, with deep expertise across platform engineering, data engineering, AI engineering, MLOps, operations research, and applied analytics. Our teams help clients move beyond platform implementation into real business transformation.

As Databricks continues to become a core enterprise AI platform, we are hiring Forward Deployed Engineers who can help clients design and deploy AI-native solutions on Databricks that create measurable business impact.

About the Role

As a Lead Forward Deployed Engineer – Databricks, you will work directly with clients to design, build, and operationalize AI and data solutions on the Databricks platform.

This role is for someone who can operate at the edge of the customer environment: understanding the business problem, assessing the data and platform architecture, designing the right technical path, and building production-grade solutions using Databricks capabilities.

You will work across modern data engineering, AI engineering, agentic workflows, semantic analytics, Lakehouse architecture, Databricks Apps, Lakebase, Genie, Mosaic AI, model serving, and production deployment patterns.

The role requires a builder’s mindset, strong client presence, and the ability to turn ambiguous business needs into deployed technical solutions.

What You Will Do

• Work directly with business and technical stakeholders to identify high-value data and AI use cases that can be delivered on Databricks
• Design, build, and deploy production-grade data and AI solutions using Databricks capabilities across the Lakehouse, Mosaic AI, Unity Catalog, Databricks SQL, Workflows, Delta Lake, Databricks Apps, Genie, Agents, and Lakebase
• Lead client discovery sessions to understand business workflows, data availability, platform maturity, integration needs, and measurable success criteria
• Architect AI-native data platforms that support agentic workflows, semantic analytics, model deployment, retrieval systems, optimization models, and operational applications
• Build Genie rooms, semantic layers using Metric Views, decision-support applications, data products, AI applications, and agent memory architectures that help clients operationalize insight and action
• Partner with data engineering, AI engineering, analytics, business, security, and governance stakeholders to design secure, scalable, production-ready solutions
• Create prototypes, demos, technical reference architectures, and reusable accelerators that showcase the value of Databricks for enterprise AI and analytics w