Required Skills: 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.
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