Lead Forward Deployed Engineer, Databricks 2026- US, UK

Aimpoint Digital is a market-leading data, AI, and operations research advisory and solution engineering firm. They are seeking a Lead Forward Deployed Engineer to design, build, and operationalize AI and data solutions on the Databricks platform, working directly with clients to create measurable business impact.

Responsibilities:

• 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 workloads
• Help clients modernize data pipelines, improve platform architecture, implement governance patterns, and deploy AI systems into operational workflows
• Work with Aimpoint Digital’s alliance, sales, and delivery teams to shape Databricks-led opportunities and translate client needs into winning solution approaches
• Develop thought leadership, solution accelerators, demos, and internal enablement materials that strengthen Aimpoint Digital’s Databricks practice

Requirements:

• Strong experience in data engineering, AI engineering, platform engineering, solution architecture, or enterprise software development
• Hands-on experience with Databricks, Spark, Delta Lake, Lakehouse architecture, data pipelines, model deployment, or modern data platform patterns
• Strong Python and SQL skills. Experience with PySpark, MLflow, Databricks Workflows, Unity Catalog, Databricks SQL, or similar tooling is strongly preferred
• Familiarity with enterprise AI patterns such as RAG, agents, model serving, vector search, semantic layers, data applications, evaluation frameworks, and governance
• Ability to work directly with clients, understand ambiguous business needs, and translate them into technical architecture and implementation plans
• Strong communication skills with the ability to engage executives, business leaders, architects, data engineers, ML engineers, and analytics teams
• Comfort moving from strategy to architecture to hands-on development
• A practical understanding of what it takes to move from demo to production in complex enterprise environments
• Databricks certification or deep hands-on delivery experience in the Databricks ecosystem
• Experience building Databricks Apps, Genie rooms, Lakebase-backed applications, Mosaic AI workflows, feature pipelines, MLflow deployments, vector search systems, or agentic solutions
• Experience with cloud platforms such as AWS, Azure, or GCP
• Experience in consulting, forward deployed engineering, solution architecture, field engineering, technical pre-sales, or client-facing delivery
• Experience designing governed data products, semantic models, operational analytics applications, or AI/ML systems
• Familiarity with industry use cases in retail and CPG, manufacturing, supply chain, energy, AI infrastructure, or private equity
• Ability to create technical architecture diagrams, delivery roadmaps, demos, sales enablement assets, and reusable solution accelerators