Applied AI Strategist, Federal

Thread AI•New York, NY
•$150,000 - $200,000

About The Position

Thread AI is hiring an Applied AI Strategist to help federal customers identify where AI can improve their work and put those capabilities into use. The role investigates customer data and processes, builds workflows in Lemma, and tests them with the people who will use them. Work may include improving handoffs between offices or helping a team turn an evaluation into a workflow used regularly. The strategist owns problem definition, workflow requirements, customer execution, and adoption. In partnership with an Applied AI Engineer, the strategist determines what to build and how to measure success; Growth handles commercial negotiations and account expansion, informed by delivery results. This is an individual-contributor role with responsibility for leading customer engagements. The role works closely with users, engineering, program leaders, and technical stakeholders. It also brings customer problems back to product and engineering, develops reusable workflows and implementation guidance, and collaborates with Growth on discovery and evaluations. The position is full-time, preferably based in New York City, and requires approximately 25–50% travel. The annual base pay range is $150,000–$200,000, plus equity. An active U.S. Secret security clearance or higher is preferred but not required. Applicants must be U.S. citizens or nationals, or U.S. lawful permanent residents.

Requirements

  • Four or more years of relevant experience, or comparable evidence of independently leading customer delivery, product implementation, or operational technology adoption.
  • A track record of taking an ambiguous problem through implementation and into sustained use, with clear evidence of what changed for users.
  • Strong analytical judgment, including the ability to investigate data, question assumptions, and turn competing requests into a manageable scope.
  • Technical fluency with APIs, data structures, and AI models; ability to follow engineering tradeoffs and learn a product well enough to build useful workflows.
  • Ability to work credibly with users, technical teams, and senior stakeholders and help them reach decisions.
  • Clear writing and practical execution, including useful requirements, decision records, training materials, and concise updates.
  • U.S. citizenship or nationality, or U.S. lawful permanent residency.

Nice To Haves

  • Experience working with federal agencies or military teams and understanding how operational users, program offices, and technical stakeholders make decisions.
  • Experience using SQL, Python, or another analytical tool to investigate data or prototype a solution.
  • Experience building or deploying AI applications, including evaluations and workflows with human review.
  • Experience helping users change established processes and measuring whether a new tool improved their work.
  • An active U.S. Secret security clearance or higher.

Responsibilities

  • Work alongside users to understand their decisions and the obstacles that consume their time; identify a problem worth solving and establish how to measure improvement.
  • Investigate available data and systems with the customer and engineering partner, surfacing access, data-quality, and integration dependencies early.
  • Build agents and workflows in Lemma, test their logic with realistic examples, review outputs with users, and refine the work.
  • Agree on scope, milestones, and acceptance criteria; keep customer decisions and dependencies moving and raise changes that affect delivery commitments.
  • Run working sessions and training to help users operate workflows independently and recognize when they need attention.
  • Measure adoption and results, and explain them clearly to users, program leaders, and technical stakeholders.
  • Bring specific customer problems to product and engineering, and develop reusable workflows and implementation guidance from successful field work.
  • Work with Growth on discovery and evaluations, using customer evidence to shape feasible follow-on work.
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