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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