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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Forward Deployed Engineer, Databricks 2026- US, UK - **Company:** Aimpoint Digital - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Computing Platforms, Automated Storage and Retrieval Systems, Microsoft Azure, Data Architecture, Information Engineering, Data Infrastructure, Data Systems, Python (Programming Language), Standard Sql, Search Technologies, Software Deployment, Software Engineering, SQL Databases, AI Infrastructure, System Availability, Apache Spark, Data Layers, Data Lakes, Pyspark, Data Management, Machine Learning Operations, Data Pipelines, Automation Anywhere, Databricks - **Published:** May 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0918a189e89da257 ## About the Role Do you have experience in SQL databases?, * 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 ## Description 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 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 ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)