Skip to content

Sr. Deployment Strategist, FDE - Public Sector

$219,765–$302,220Washington, DCSenior

View posting at Databricks

This job is no longer in our list. Last seen 2026-09-22. Check the employer’s posting for availability.

About the job

Own end-to-end product and technical direction for high-value, C-suite-sponsored public-sector AI engagements, from discovery and MVP definition through production launch, adoption, and strategic handoff.

Summary written from the posting.

What you’ll do

  • Scope C-suite-sponsored customer problems, quantify value, and define pilots, MVPs, success criteria, and timelines.
  • Author PRDs, prioritize engineering backlogs, manage scope, and translate business needs into technical requirements.
  • Lead FDE delivery, architecture reviews, stakeholder alignment, risk identification, and technical issue resolution.
  • Own production launch, readiness, adoption, user feedback, and proof of business value.

What you’ll bring

  • Typically 7+ years delivering complex customer-facing data, analytics, AI, or software engagements, or equivalent founder or technical-builder experience.
  • Experience delivering data, machine learning, or generative AI systems into production.
  • Proficiency in at least one of Python, Java, or SQL, with ability to explore data, review code and pipelines, prototype, and troubleshoot.
  • Fluency in modern data and AI architectures, including data pipelines, distributed systems, security, governance, machine learning, and generative AI patterns.

Technologies

Python · Java · SQL · data pipelines · distributed systems · machine learning · generative AI · notebooks · PRDs

About Databricks

Unified Data + AI Platform that runs analytical and operational workloads on an open, governed foundation for data engineering, BI, analytics, machine learning, and enterprise AI applications.

Private Late · 5000+ people

Pay and conditions

Posted pay
$219,765–$302,220
Pay details

$219,765—$302,220 USD

Location
Washington, DC
Experience requirements
7+ years

The work, as we read it

Kind of work
Plans what the customer deploys first

Our reading of the posting, not the employer’s words.