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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # DoD MLOps Software Engineer - **Company:** Charles River Analytics Inc. - **Location:** United States - **Experience:** Expert - **Salary:** $140,000.0 - $225,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Configuration Management, System Configuration, Continuous Integration, Software Debugging, Monitoring of Systems, JSON, Python (Programming Language), SQL Databases, YAML, Reinforcement Learning, Data Logging, Scripting, Large Language Models, Multi-Agent Systems, Model Validation, Git, Containerization, Kubernetes, Bug Reporting, Information Technology, Build Tools, Virtual Agents, Docker - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/dod-mlops-software-engineer-charles-river-analytics-8732428 ## About the Role * 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 * 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 We prefer to see: * 5+ years of experience in artificial intelligence, with a focus on agent-based simulation * Experience with agent-based modeling, AI-enabled simulations, decision-support tools, wargaming systems, and human-machine teaming * Proficient in domain-specific languages (DSLs), scripting languages, behavior trees, rule engines, planning systems, multi-agent systems, and simulation configuration languages * Skilled in Python, YAML/JSON, SQL, Git, CI/CD pipelines, testing frameworks, logging, tracing, and configuration management * Familiar with large language model (LLM)-enabled agents, symbolic AI, planning algorithms, reinforcement learning, behavior modeling, and cognitive architectures, as they pertain to architecture * Experience in military analysis, campaign analysis, mission analysis, operational planning, or experimentation * Knowledge of AI risk management, model evaluation, traceability, human oversight, and responsible AI documentation ## Description Our ideal candidate is much more than a typical data analyst or AI researcher. We are looking for a customer-facing applied AI and wargaming analyst who can effectively represent military decision problems, behaviors, constraints, objectives, and workflows within a proprietary agent-based simulation architecture. If you're interested in answering this challenge, we'd love to hear from you. 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