AI/ML Software Engineer

• Design and implement APIs, data pipelines, and simulation runtime logic that connect and enable mission applications.
• Develop software using modern programming languages such as Java, Python, C++, or TypeScript/Angular.
• Write clean, testable, and maintainable code following secure coding and software engineering best practices.
• Build and integrate modular microservices to improve scalability, maintainability, and interoperability.

Cloud & Containerized Environments

• Build and deploy containerized, cloud-native services using Docker, Kubernetes, and CI/CD pipelines (GitLab, Jenkins, or equivalent).
• Implement Infrastructure-as-Code and automation scripts to accelerate deployment and configuration management.
• Contribute to secure deployments across hybrid or disconnected environments (IL4-IL6, AWS GovCloud, or on-prem).

Systems Integration & Distributed Computing

• Develop distributed systems and data integration frameworks using message buses such as Kafka or Redis.
• Engineer data flow between analytic, AI, and simulation components to support real-time mission use cases.
• Collaborate with system engineers and architects to ensure interoperability across software ecosystems.

Data & Analytics Integration

• Build and manage databases (PostgreSQL, MongoDB, graph DBs) and model complex data relationships.
• Develop data services that feed analytics pipelines or integrate AI/ML outputs into runtime systems.
• Work with serialization and exchange formats such as JSON, Protobuf, GeoJSON, or KML.

Security, Testing & Sustainment

• Write, test, and deploy software within secure or classified environments.
• Automate testing and monitoring to ensure performance, reliability, and repeatable deployments.
• Support the transition of prototypes to operational systems, focusing on maintainability and observability.

• Must be a U.S. citizen and be willing to obtain and maintain a secruity clearance, as needed.
• 4-6 years of professional software engineering experience.
• Strong full-stack or systems engineering background.
• Proficiency in one or more of the following: Java, Python, C++, or TypeScript/Angular.
• Experience building containerized, cloud-native solutions using Docker, Kubernetes, and CI/CD pipelines.
• Understanding of distributed systems and message buses (Kafka, Redis, etc.).
• Exposure to DevSecOps, Zero-Trust, or ATO/RMF processes in DoD environments.

Preferred Qualifications:

• Experience developing or integrating analytics and AI models into production systems.
• Familiarity with databases such as PostgreSQL, MongoDB, or graph databases.
• Experience deploying code in IL4-IL6 or edge/disconnected environments.
• Knowledge of Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
• Active Secret clearance (TS/SCI preferred).
• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.