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Anduril's Lattice software platform integrates together many sensors into a single cohesive view of the world, providing needed context for our users. Anduril's Frontier AI team builds edge-compatible, generative AI systems into the Lattice software platform to provide features and products that improve autonomy and reduce cognitive burden on the warfighter. Specific applications include but are not limited to automating mission planning, battle-space understanding, voice-control of assets, and enabling higher-levels of autonomy. 

Anduril is looking for a full-stack software engineer to build agentic modeling and simulation systems for operational planning. This role sits at the intersection of applied AI, backend systems, model and simulation, wargaming, and mission software. You will build the systems that let humans and AI agents author scenarios, task simulated entities, inspect simulation state, reason about human and adversary behavior, and evaluate courses of action in near real time. The goal is to shorten military planning cycles from days to minutes by putting physics-backed simulation and AI-assisted planning directly in the hands of operators.

• Build agentic workflows that make modeling and simulation capabilities accessible through natural language, structured tools, APIs, and operator-facing product experiences.
• Design multi-agent architectures that model human decision-making, adversary responses, operational constraints, and plan tradeoffs across complex military operations.
• Integrate LLM tool use, function calling, retrieval, planning loops, evaluation hooks, and guardrails with simulation engines, physics/modeling backends, and mission planning systems.
• Build backend services and interfaces for scenario creation, entity tasking, simulation state retrieval, course-of-action generation, plan comparison, and real-time analysis.
• Partner with warfighters, model/sim experts, autonomy engineers, game/simulation engineers, and mission software teams to translate ambiguous planning workflows into reliable software.
• Improve observability, reproducibility, and evaluation for agent behavior so generated scenarios and recommendations are inspectable, explainable, and operationally useful.
• Learn and apply relevant DoD modeling and simulation tools and concepts, including campaign-level simulation, mission-level simulation, wargaming workflows, and systems such as AFSIM and STORM.

• Strong production software engineering experience building backend services, APIs, platforms, or integrations around complex stateful systems.
• Hands-on experience building AI/ML or LLM-powered software, ideally including tool/function calling, RAG, structured outputs, agent orchestration, MCP-style interfaces, or model evaluation.
• Proficiency in Python, Go, or a similar backend language, with the ability to work across service boundaries and integrate with external systems.
• A degree in Computer Science, Software Engineering, Mathematics, Physics, or a related technical field.
• Ability to work directly with operators, warfighters, and technical SMEs to turn ambiguous operational planning needs into concrete product and engineering requirements.
• Strong judgment around reliability, safety, observability, and debugging for AI systems deployed in high-stakes environments.
• Eligible to obtain and maintain an active U.S. Top Secret security clearance.

• Experience with modeling and simulation, physics engines, wargaming tools, autonomy simulation, operations research, planning systems, or human/adversary behavior modeling.
• Experience with DoD modeling and simulation tools or concepts such as AFSIM, STORM, campaign-level simulation, mission-level simulation, or course-of-action analysis.
• Experience shipping production agentic systems, not only prototypes.
• Familiarity with gRPC/protobuf, Kubernetes, containerized deployments, distributed systems, observability, and secure or air-gapped environments.
• Experience in defense, aerospace, autonomy, robotics, gaming/simulation, command-and-control, or operational planning domains.