MLOps Engineer — AI Agent Simulation for Defense

Charles River Analytics; Honolulu (HI); On-site; USD 140,000 - 225,000; Full time

Benefits offered by this job

100% employer-paid medical & dental

Vision, life and disability insurance

Maternity/paternity leave

Tuition reimbursement

Gym allowance

Paid time off

Casual environment

Job summary

Charles River Analytics, a GRVTY company, seeks an MLOps Software Engineer to join a customer on-site as an embedded technical analyst. You will customize AI agent training configurations and tailor agent-based simulation backends for military wargaming and analysis.

Ideal candidates combine applied AI and wargaming experience, can translate decision problems into DSL logic, and collaborate with customers and engineers to improve product capabilities while ensuring robust deployment, security

Qualifications

• Bachelor's degree in computer science or related field; a graduate-level degree is preferred.
• Experience in AI, 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
• Capability to read, write, customize, test, and document a specialized language or configuration grammar used to express wargaming logic
• 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
• Ability to configure agent runtime settings, data/context sources, tool access, execution parameters, integration points, and versioned baselines
• Proficient in explaining complex agent behaviors and domain-specific language (DSL) logic to non-developer military users, as well as communicating field issues to engineering teams
• Capacity to translate customer needs and observed shortfalls into product requirements, bug reports, feature requests, and acceptance criteria
• Active or eligible for a security clearance, as required by contract

Responsibilities

• Customize AI agent training configurations and tailor agent-based simulation backends to support military wargaming and analysis
• Help customers define analytical problems, code agent behavior and decision-making logic, configure the agent backend, evaluate agent outputs
• Identify shortcomings in the domain-specific language or agent architecture for the product development team
• Represent military decision problems, behaviors, constraints, objectives, and workflows within a proprietary simulation architecture
• Translate customer needs into product requirements, bug reports, feature requests, and acceptance criteria

Skills

AI agent RL

Agent-based simulation

Docker

Kubernetes

Cloud deployment

AWS GovCloud

CI/CD pipelines

Python

YAML/JSON

SQL

Git

Logging/Monitoring

DSLs

Education

Bachelor's degree in computer science or related field

Graduate-level degree preferred

Tools

Docker

Kubernetes

Git

CI/CD

Logging tools

Job description

Charles River Analytics, a GRVTY company, seeks an MLOps Software Engineer to join a customer on-site as an embedded technical analyst. You will customize AI agent training configurations and tailor agent-based simulation backends for military wargaming and analysis.

Ideal candidates combine applied AI and wargaming experience, can translate decision problems into DSL logic, and collaborate with customers and engineers to improve product capabilities while ensuring robust deployment, security