AI and ML Engineer

Booz Allen Hamilton•Arlington, VA

8h•Remote

About The Position

As an AI / ML engineer, you know that organizing data and architecting intelligent models can yield pivotal insights when gathered from disparate sources. We need a technically skilled AI / ML engineer like you to help our customer build intelligent systems and find answers in their data to impact important missions, from enterprise network operations to securing the homeland. As an AI / ML engineer at Booz Allen, you’ll help build advanced technology solutions and implement ML activities on some of the most mission-driven projects in the industry. You possess a high degree of self-agency, thriving in environments where you are trusted to "figure things out" with a high degree of autonomy. You’ll bring a scrappy, technically curious approach as you code, deploy, and develop AI / ML pipelines, models, and applications that organize and make disparate data meaningful. Here, you’ll work with and guide a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You are eager to learn and will use your hands-on coding expertise in analytical exploration, model development, and data examination while you manage the assessment, design, building, and maintenance of scalable AI / ML applications and solutions. Work with us to solve real-world challenges for the Army. Join us. The world can’t wait.

Requirements

5+ years of experience architecting and delivering AI-enabled mission or enterprise systems, including data integration, secure compute, and user-facing applications across restricted or classified environments
5+ years of experience designing and implementing data pipelines, ontologies, and application workflows on platforms such as Palantir Foundry or Gotham, including air gapped, degraded connectivity, or multiclassification deployments
5+ years of experience building secure analytics ecosystems, including log pipelines, monitoring frameworks, or network operational dashboards, whether greenfield or migrated from legacy tooling
5+ years of experience with DevSecOps practices such as containerization, orchestration, CI / CD, and automated testing adapted for limited toolchain environments where standard pipelines don’t fully apply
5+ years of experience integrating AI / ML capabilities into production workflows or operator tooling, including LLM-backed assistants, model augmented decision aids, or automation that expands what a small team can deliver
Ability to quickly learn unfamiliar technologies, develop real hands-on mastery, and lead engineers through full implementation with confidence
TS/SCI clearance
Bachelor’s degree

Nice To Haves

Experience working across multiple clouds, enclaves, or classification levels on the same program, including translating architectures between NIPR, SIPR, JWICS, or local, state, or federal equivalents
Experience on major defense programs or with large systems integrators, delivering mission capability while navigating bureaucratic, acquisition, or compliance friction
Experience supporting DoD installations, operational units, or C2 systems especially when the inherited environment was undocumented, partially broken, or technically inconsistent
Experience building agentic workflows, automation pipelines, or custom tooling that materially increased engineering throughput or reduced operator friction
Experience in a senior technical lead or architect role where you were accountable for both the design and successful delivery of the system
Master’s degree
AWS, Palantir Foundry or Gotham, Kubernetes, or similar Architecture Certifications

Responsibilities

Code, deploy, and develop AI / ML pipelines, models, and applications that organize and make disparate data meaningful.
Manage the assessment, design, building, and maintenance of scalable AI / ML applications and solutions.
Work with and guide a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment.
Use hands-on coding expertise in analytical exploration, model development, and data examination.