DoD MLOps Software Engineer

About the role

The role involves customizing AI agent training configurations and tailoring agent-based simulation backends to support military wargaming and analysis. Responsibilities include defining analytical problems, coding agent behavior and decision-making logic, configuring the agent backend, evaluating agent outputs, and identifying shortcomings in the domain-specific language or agent architecture.

Responsibilities

• Helping customers define analytical problems, behaviors, constraints, objectives, and workflows within a proprietary agent-based simulation architecture.
• Coding agent behavior and decision-making logic.
• Configuring the agent backend.
• Evaluating agent outputs.
• Identifying shortcomings in the domain-specific language or agent architecture.
• Representing military decision problems, behaviors, constraints, objectives, and workflows within a proprietary agent-based simulation architecture.

Requirements

• Bachelor's degree in computer science or a related field; a graduate-level degree is preferred.
• Experience in artificial intelligence, with a focus on AI agent reinforcement learning and agent-based simulation.
• Proficiency in understanding and configuring agent roles, goals, behaviors, interactions, state, decision logic, and emergent behavior within a simulation environment.
• Experience with deployment engineering (e.g., build systems and containerization), Docker, Kubernetes, cloud-deployment (e.g., AWS gov cloud), and proficient with logging and monitoring systems to maintain high up time.
• Experience working with customers to define analytical questions, decision contexts, assumptions, measures, constraints, and experimental designs.
• Skills in testing agent behaviors, inspecting traces, debugging unexpected outcomes, documenting uncertainties, and clearly communicating limitations.
• Experience configuring agent runtime settings, data/context sources, tool access, execution parameters, integration points, and versioned baselines.
• Ability to translate customer needs and observed shortfalls into product requirements, bug reports, feature requests, and acceptance criteria.

Qualifications

• Active or eligible for a security clearance, as required by contract.

Skills

• Python, YAML/JSON, SQL, Git, CI/CD pipelines, testing frameworks, logging, tracing, and configuration management.
• Familiarity with large language model (LLM)-enabled agents, symbolic AI, planning algorithms, reinforcement learning, behavior modeling, and cognitive architectures, as they pertain to architecture.
• Knowledge of AI risk management, model evaluation, traceability, human oversight, and responsible AI documentation.

Benefits

• Salary Range: $140,000 - $225,000
• Substantial total rewards, including bonus and retirement contribution, with an attractive benefits package including 100% employer-paid medical and dental insurance, as well as vision, life, and disability insurance, paid maternity/paternity leave, tuition reimbursement, monthly gym allowance, free parking, generous paid time off, and a casual environment.
• Accessible by public transportation.
• Charles River became an employee-owned company in 2012, to set the stage for the next-generation of innovation, service, and growth in R&D.
• Gained the scale and capacity to transition, field, and sustain our innovations faster and more effectively than ever before with the joining of GRVTY.