AI Developer

Booz Allen Hamilton•San Antonio, TX

About The Position

AI Developer The Opportunity : As an experience d AI engineer, you know that AI systems are critical to understanding and processing massive datasets in an organization. Your ability to c ond uct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support optimizing organizational efficiency. As an AI Developer on our Air Power team, you’ll train, test, deploy, and maintain models that learn from data. In this role, you’ll own and define the direction of mission-critical solutions by applying cutting-edge Agentic frameworks. You’ll be part of a large community of AI professionals across the company and collaborate with data engineers, data scientists, solutions architects, and product owners to deliver world-class solutions to transform how the Air Force manages its day-to-day business. Your skills and extensive technical expertise will guide clients as they navigate the landscape of Agentic Frameworks. Work with us to solve real-world challenges and define ML strategy for the Department of War . Join us. The world can’t wait.

Requirements

Experience building production-grade sof t war e in Python, TypeScript, or Java with APIs and data services, including FastAPI, Flask, REST, GraphQL, or SQL, and sof t war e engineering fundamentals, including testing, code review, and CI / CD
Experience developing and deploying AI-enabled applications such as LLMs, RAG, GraphRAG, agentic workflows, or tool-calling to solve mission problems in industry, government, or national security
Experience building secure data foundations on enterprise cloud platforms such as AWS, governed ingest and file exchange, data catalog and met adata, and data mesh-style data products to enable reuse across teams and bases
Experience designing event-driven integrations and workflow automation such as asynchronous messaging, job orchestration, or audit logging to move from insight to action
Experience implementing MLOps or DevSecOps practices such as CI / CD, containerization, automated testing, or model evaluation and monitoring in constrained or regulated environments
Experience partnering with domain SMEs such as civil engineers to translate tacit knowledge into explicit playbooks, decision logic, and human-in-the-loop tools that improve proficiency and consistency
Secret clearance
Bachelor’s degree in Computer Science, Sof t war e Engineering, or Data Science and 5+ years of experience in computer science, sof t war e engineering, or data science, OR Master’s degree in Computer Science, Sof t war e Engineering, or Data Science and 2+ years of experience in computer science, sof t war e engineering, or data science

Nice To Haves

Experience working with geospatial or 3D data, including point clouds, LiDAR, or photogram met ry, or digital-twin or facility and asset data models
Experience with knowledge -centric data systems such as vector databases, knowledge graphs, or semantic search to improve information findability and decision support
Experience integrating sensor streams or IoT tele met ry and edge-to-cloud data flows such as Kafka, NATS, RabbitMQ, or equivalent for asset monitoring and situational a war eness
Experience deploying sof t war e and data or ML pipelines in disconnected, air-gapped, or classified environments
Experience with cross-domain data handling constraints
Experience with Kubernetes or OpenShift, cloud-native patterns, and Infrastructure as Code, including Terraform, in DoD or IL environments
Experience with RMF or STIG-aligned delivery
Experience with AI-assisted sof t war e development tools and practices such as code copilots, automated tests, or secure-by-design patterns to increase delivery velocity responsibly
Experience developing computer vision and multimodal analytics pipelines, including imagery segmentation or classification, point cloud processing, and report generation, and integrating outputs into downstream workflows