You'll develop the backend infrastructure that interfaces with agentic AI and machine learning pipelines to support platform, sensor, behavior, and decision models used across the simulation, while building extensible, well-tested foundations for the broader wargaming platform. You'll help design scenario-generation, Monte Carlo, sensitivity-analysis, and campaign-evaluation workflows, and build the distributed, cloud-scale infrastructure that lets simulations run across developer workstations, on-premises infrastructure, and cloud compute while preserving reproducibility and model provenance. Strong command of cloud services and distributed architectures is essential.

Design and implement backend services and APIs that orchestrate mission- and campaign-level simulation runs, collect their outputs, and expose results to analysts and government stakeholders.

Build scenario-generation, operational and mission planning workflows, and key services for Monte-Carlo based sensitivity-analysis for our wargaming and decision-support platform.

Build distributed, cloud-scale infrastructure that scales simulations across developer workstations, on-premises infrastructure, and cloud compute while preserving reproducibility and model provenance.

Build data ingestion, normalization, and analysis pipelines that turn raw simulation output into decision-ready insight for defense users.

Build scalable APIs (REST, GraphQL, gRPC) and containerized services that connect the Python tooling layer to the core simulation runtime and downstream analysis tools.

Gather requirements from government stakeholders, domain experts, and analysts, and distill them into clear software designs.

Employ strong SDLC practices throughout — code review, testing, continuous integration, release management, and build systems.

Staff Python Engineer (Modeling & Simulation)

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Code Metal

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