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August Schell is looking for an AI Delivery Engagement Lead to sit at the front edge of an Intelligence Community customer's adoption of commercial AI. This is the seat between a fast-moving AI platform and the mission users who have to trust it: you scope the use cases, run the delivery, and own the relationship — translating what the analysts actually need into what the platform actually does, and back again.
This is not a data-science bench role and it is not a project-administration role. It is a customer-facing delivery seat for someone technical enough to be credible in an engineering conversation and social enough to be the person the customer asks for by name.
Individuals in this role must hold an active TS/SCI with Full Scope Polygraph and be able to work on site in McLean, VA.
Responsibilities
Scope AI and agentic-workflow use cases directly with mission customers — find the operational pain, size it, and shape it into something deliverable
Own delivery end-to-end for those use cases: requirements, sequencing, cross-functional coordination, and the status conversation with the customer
Lead cross-functional teams spanning platform engineering, data operations, and government stakeholders — without formal authority over most of them
Serve as the customer's primary point of contact — run onboarding, manage relationship health, and surface risk before it becomes a problem
Translate in both directions: mission requirements into technical scope for the engineering team, and technical constraints into plain language for government leadership
Work model and data operations problems hands-on where needed — evaluation, quality, human-in-the-loop workflow design, and the operational plumbing around a model in production
Identify patterns worth standardizing and turn one-off delivery wins into a repeatable motion across the customer's organization
Grow the account: spot adjacent use cases and expand the footprint from a first win into a program
Requirements
Active TS/SCI clearance with Full Scope Polygraph — current and in scope
Experience working at or with this customer — you know the environment, the pace, and how work actually gets approved and fielded there
A real appetite to learn and chase this — commercial AI inside the fence is new ground for everyone; we are looking for someone who wants to be early, not someone waiting for a mature playbook
Ability to work on site in McLean, VA
A technical foundation you can stand on — computer science, engineering, data science, statistics, economics, or equivalent hands-on experience. A formal AI/ML background is welcome but not required; the willingness to get deep in it is
Structured problem solving — able to take an ambiguous mission problem and turn it into a scoped plan
Strong written and verbal communication; comfortable briefing both engineers and senior government leadership
Willingness to travel approximately 25% and to be forward-deployed to the customer's site
Stand out with
Hands-on experience with modern AI/ML already — large language models, agentic workflows, model evaluation, prompt and context engineering, or the operational realities of running models against real data
Python and/or SQL proficiency — you can pull the data and check the answer yourself
MLOps and model operations experience: evaluation pipelines, data labeling and quality, human-in-the-loop workflow design, monitoring in production
Experience at an API or platform technology company — you know how a product team thinks and how to feed it
Computer vision, ISR/FMV analytics, or multi-INT data experience
A track record of expanding a client relationship from one use case into a program
Cloud and data platform experience at classified levels
A track record of building the second version of something — documentation, playbooks, and templates that outlive the first engagement