• A master’s degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with demonstrated experience working on or developing AI/ML capabilities.
• At least four years of relevant AI/ML experience that includes work with large language models, retrieval-augmented generation, and prompt engineering.
• Hands-on experience integrating LLM-enabled software and RAG capabilities into applications or workflows.
• Developing or supporting agentic-AI capabilities and multi-step AI workflows.
• Designing, building, or supporting inference pipelines.
• Ability to evaluate AI-enabled capabilities and clearly document findings, design decisions, and results.
• Testing and documenting AI-enabled software capabilities.
• Ability to clearly explain your personal technical ownership and contributions.
• Strong collaboration and technical-communication skills.

Preferred Background

Experience with several of the following can strengthen your fit:

• Moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software workflows.
• Evaluating grounding, reliability, output quality, hallucinations, or other limitations of AI-enabled systems.
• Integrating AI services with backend APIs or established software applications.
• Secure software-development lifecycle and DevSecOps practices.
• OpenShift, Kubernetes, CI/CD, or containerized application delivery.
• Secure, restricted, disconnected, on-premises, or classified development environments.
• Defense, government, aerospace, mission-planning, or other regulated environments.
• Collaboration with software-engineering, cybersecurity, platform, and customer-facing technical teams.