Lead AI Forward Deployed Engineer - Databricks
ON Data Staffing
Job Description
Lead AI Forward Deployed Engineer – Databricks
\n \nON Data Staffing is partnering with a leading Data & AI consultancy to recruit an experienced Lead AI Forward Deployed Engineer – Databricks to join their growing consulting practice.
\nThis is a senior, highly client-facing engineering role focused on designing, building, and deploying AI-native solutions on Databricks .
\nYou'll work directly with enterprise clients to understand complex business problems, assess their data and AI architecture, define the right technical approach, and build production-grade AI solutions that create measurable business impact.
\nThis role combines AI Engineering, Data Engineering, Solution Architecture, and hands-on development , so we're looking for someone who can move comfortably from client discovery and architecture through to building and deploying the solution.
\n \nWhat You'll Be Doing
\n- \n
- Work directly with business and technical stakeholders to identify high-value AI and Data use cases \n
- Design, build, and deploy production-grade AI solutions on Databricks \n
- Lead client discovery sessions covering business workflows, data availability, AI opportunities, platform maturity, integrations, and success criteria \n
- Architect AI-native data platforms supporting agentic workflows, RAG, semantic analytics, model deployment, retrieval systems, and operational AI applications \n
- Build solutions using Mosaic AI, Databricks Agents, Model Serving, Vector Search, MLflow, Unity Catalog, Databricks Apps, Genie, and Lakebase \n
- Develop AI agents, RAG applications, semantic layers, data products, and decision-support applications \n
- Partner with AI Engineering, Data Engineering, Analytics, Security, and Governance teams to deliver secure and scalable AI solutions \n
- Build prototypes, AI demos, technical reference architectures, and reusable accelerators \n
- Take AI solutions from proof of concept through to production \n
- Support technical pre-sales and help shape AI and Databricks-led client opportunities \n
- Contribute to technical thought leadership and the continued development of the wider AI & Databricks practice \n
What We're Looking For
\nWe're looking for an experienced AI Engineer / Forward Deployed Engineer who combines strong Databricks expertise with a builder's mindset and excellent client-facing skills.
\nYou'll ideally have:
\n- \n
- Strong experience across AI Engineering, ML Engineering, Data Engineering, Solution Architecture, or Software Engineering \n
- Hands-on experience building and deploying AI/ML solutions on Databricks \n
- Strong Python and SQL skills \n
- Experience with Mosaic AI, MLflow, model deployment, Databricks Workflows, and Unity Catalog \n
- Experience with modern enterprise AI patterns including RAG, AI Agents, model serving, vector search, semantic layers, and evaluation frameworks \n
- Experience translating ambiguous business problems into technical AI solutions \n
- Strong communication skills with the ability to engage executives, architects, engineers, and business stakeholders \n
- The ability to move comfortably between strategy, architecture, and hands-on AI engineering \n
- Experience taking AI solutions from prototype through to production \n
AI & Databricks Experience
\nExperience across the following would be highly desirable:
\n- \n
- Generative AI and RAG \n
- AI Agents and agentic workflows \n
- Mosaic AI \n
- Databricks Agents \n
- Model Serving \n
- Vector Search \n
- MLflow \n
- Databricks Apps \n
- Genie \n
- Lakebase \n
- Feature pipelines and feature stores \n
- Semantic layers and analytics \n
- AI evaluation, monitoring, and governance \n
- Production ML and AI deployment patterns \n
Ideal Background
\n- \n
- Previous experience within Consulting, Professional Services, Forward Deployed Engineering, AI Engineering, Solution Architecture, or technical client delivery \n
- Strong hands-on Databricks and AI/ML delivery experience \n
- Databricks certifications are highly desirable \n
- Experience with AWS, Azure, or Google Cloud Platform \n
- Experience designing and deploying production GenAI, ML, or agentic AI systems \n
- Comfortable creating architecture diagrams, technical roadmaps, prototypes, demos, and reusable AI accelerators \n
- Strong understanding of building secure, governed, scalable, production-ready AI systems \n
- Passion for helping enterprise organisations use Databricks as the foundation for enterprise AI at scale \n
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