About the job
As an experienced AI engineer, you know that AI systems are critical to understanding and processing massive datasets in an organization. Your ability to conduct 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.
Responsibilities
Own and define the direction of mission-critical solutions by applying cutting-edge Agentic frameworks. 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. Guide clients as they navigate the landscape of Agentic Frameworks. Solve real-world challenges and define ML strategy for the Department of War.
Qualifications
Minimum
Experience building production-grade software in Python, TypeScript, or Java with APIs and data services, including FastAPI, Flask, REST, GraphQL, or SQL, and software 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 metadata, 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
Preferred
Experience working with geospatial or 3D data, including point clouds, LiDAR, or photogrammetry, 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 telemetry and edge-to-cloud data flows such as Kafka, NATS, RabbitMQ, or equivalent for asset monitoring and situational awareness
Experience deploying software 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 software 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