Principal Python Engineer, Code Metal

• Professional experience with collaborative, enterprise-level software development in Python, delivering products to a large customer base
• Experience gathering requirements from stakeholders and distilling them into software designs
• Experience building and delivering robust software using strong SDLC practices, including code review, testing, continuous integration, release management, and build systems
• Familiarity with machine learning tools and frameworks
• Expertise building scalable APIs (REST, GraphQL, gRPC)
• Hands-on experience with Docker and containerized application development
• Eligible to obtain and maintain an active U.S. Top Secret security clearance
• Years of Experience: 10+
• Engineering Craft & Code Quality: Sets the quality and correctness bar across the department; their work is the example others learn from; improves the automated systems and practices that ensure quality department-wide
• Architecture & Technical Knowledge: Provides architectural guidance across the department and invents paradigms that solve CodeMetal-specific domain problems (e.g., translation, optimization, deployment across target environments); a key resource on every major system
• Delivery, Scoping & De-risking: A consistent contributor to the company's technical roadmap; gives reliable estimates for large cross-team initiatives; ensures pragmatic scoping toward the most valuable outcomes
• Technical Leadership & Mentorship: An active driver of company-wide architectural reviews and proposals; mentors mid-level and senior staff at scale; influences others across departments toward the best technical outcome

Desirable

• Our Modeling & Simulation team is building the next-generation wargaming and decision-support platform that helps the DoW make multi-billion-dollar force-design decisions before those decisions are made in the real world
• The team spans simulation and physics, backend and data systems, frontend and geospatial visualization, and AI systems, working together to turn operational questions into extensible, mission- and campaign-level simulations that government users can trust
• In this role, you will help build the Python services, pipelines, and tooling that drive the core wargaming simulation
• You will design backend services and APIs that interface with the frontend, integrate with multiple simulators, manage the data, and expose results to analysts, model developers, and government stakeholders
• Scope of ownership, architectural authority, and mentorship responsibility scale with level — see “Level Expectations by Track” below
• 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