• Collaborate with Agentic AI Scientists to build and securely deploy AI agents to automate and optimize labor intensive workflows • Support both R&D tasks and direct customer engagements to speed the transition delivery of novel applied research solutions onto direct contracts • Design, implement, and maintain tools that enable agent deployments using MLOps best practices in scalable cloud infrastructure • Develop and document processes that enable secure automated development and deployment of AI agents • Design, build, train, and evaluate Machine Learning models • Build repeatable Machine Learning pipelines for model training, evaluation, deployment, and monitoring • Perform R&D to enable AI Observability and performance metrics • Design, implement, and manage cloud resources for MLOps infrastructure • Operationalize production AI/ML systems by implementing model serving, monitoring, data and model drift detection, logging, and lifecycle management to ensure reliability, scalability, and maintainability • Work in a team of AI/ML researchers and engineers using Agile development processes