Design and implement production-grade LLM and agentic systems that ingest operational, doctrinal, and policy data and transform it into structured tasks, workflows, and resource-aware plans.
Build orchestration layers across workflows, tools, and human approvals to support a recommendation-first AI copilot with progressive, user-authorized agentic actions.
Implement RAG pipelines over doctrine, regulations, and historical data to enable constraint-aware reasoning, sequencing logic, and transparent, explainable recommendations.
Design trust, permissioning, and rollback mechanisms that adapt system autonomy based on user behavior, experience, and operational risk.
Instrument systems for auditability, traceability, and user trust, ensuring all outputs can be explained and linked back to source inputs.
Optimize AI systems for latency, cost, reliability, and explainability in real-world operational environments.
Collaborate closely with product, UX, engineering, and domain experts to translate complex operational workflows into scalable, human-centered AI systems.

Requirements

Strong hands-on experience with developing and deploying LLM-based systems in production
Experience building multi-step agentic AI systems
Experience in MLOps, automating the process of training and deploying models and supportive architecture
Must have experience with containerization approaches such as Docker and Kubernetes
Developed CI/CD pipelines for testing and automation
Experience in developing or utilizing third party solutions to evaluate and quantify model performance
Proficiency in Python
Experience with: LLM orchestration, RAG architectures, Function/tool calling, State management across AI workflows, Vector Databases
Ability to reason about constraints, optimization, and dependencies
Comfort operating in ambiguous, fast-moving product environments

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

LLM-based systemsMLOpscontainerizationDockerKubernetesCI/CD pipelinesPythonRAG architecturesVector Databasesstate management

Soft Skills

reasoning about constraintsoptimizationdependenciesoperating in ambiguitycollaborationuser-centered design