Head of AI Forward Deployed Engineering (FDE), Public Sector
Databricks
| Company | Databricks |
| Category | Engineering |
| Location | Maryland; Virginia; Washington |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Director |
| Salary | Not stated by the employer |
| Posted | 12 Jun 2026 |
| Last verified | 11 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
CSQ227R77
PLEASE NOTE: Due to federal contract requirements and client site access obligations, an active U.S. government security clearance is required. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active secret or higher clearance are strongly encouraged to apply.
Mission
The Public Sector AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services (PS) engagements to help our customers build and productionize first-of-its-kind AI applications with a focus on GenAI. We work cross-functionally to shape long-term strategic priorities and initiatives alongside AI Product, Research, and Engineering.
We are looking for a world-class leader to lead and grow our AI FDE Public Sector team. In this role, you will lead public sector customers on their AI transformation with Databricks, push the boundaries of our product, recruit and develop top AI engineers, and manage a portfolio of key accounts. You will report directly to the Head of Public Sector, FDE.
The impact you will have:
Lead and scale a world-class AI FDE team, including hiring, mentoring, and building a team structure to support long-term growth and execution at scale
Develop and expand executive relationships with key customers and partners (including VP+, CIO/CDO-level stakeholders), acting as a trusted advisor during complex technical engagements and AI transformations
Align with Field Engineering and Sales Leaders to define joint strategies for strategic accounts and ensure strong delivery coordination across functions
Lead strategic AI initiatives, practice development, and standardized delivery processes; design scalable engagement models and reusable solutions for repeatability across the global team
Shape cross-functional collaboration by influencing Product, R&D, and GTM, ensuring voice-of-customer insights and delivery learnings help inform the product roadmap and GTM strategy
Own OKRs for AI-services led accounts, revenue, utilization, and public references
Represent Databricks as a thought leader in AI
What we look for:
Passion for transforming the public sector with data and AI
Extensive experience managing, hiring, and building a team of high-performing data scientists/ML engineers and leaders, with a track record of scaling organizations through developing scalable processes and cultivating leaders
Ability to scope, guide, and sell technical engagements, manage escalations, and ensure successful delivery in enterprise environments
Deep technical expertise in ML, GenAI, and data science, and curiosity to continue to stay up-to-date in this ever-changing field
Experience leading teams building cutting-edge production AI solutions in cloud environments (AWS, Azure, or GCP)
Proven success developing strategy with senior executive stakeholders to define program-level goals, align technical vision, and build trust throughout complex enterprise engagements
Demonstrated experience in cross-functional leadership roles, collaborating with Sales, Product, and GTM teams to drive business impact through AI
“Company-first” mindset
Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
Preferred:
Experience in a customer-facing consulting or professional services leadership role
Experience working with Databricks
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, inclu