Staff Python Engineer – Modeling, Simulation

Jobtailor; California (MO); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking a senior backend engineer to design and implement scalable backend services and APIs for defense-related simulation platforms. The role emphasizes Python development, robust SDLC practices, and cloud-scale infrastructure across on-premises and cloud environments.

You will work with stakeholders to translate requirements into software designs, build Monte Carlo analysis workflows, and ensure simulation reproducibility, with opportunities to mentor staff and contribute

Qualifications

• Professional experience with collaborative, enterprise-level software development in Python.
• 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, CI, 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.
• Staff level expectation: 7+ years of experience.

Responsibilities

• Design and implement backend services and APIs orchestrating mission- and campaign-level simulation runs
• Collect simulation outputs and expose results to analysts and government stakeholders
• Build scenario-generation, operational and mission-planning workflows
• Build Monte Carlo-based sensitivity-analysis services
• Build distributed, cloud-scale infrastructure across developer workstations, on-premises infrastructure, and cloud compute
• Preserve simulation reproducibility and model provenance
• Build data ingestion, normalization, and analysis pipelines producing decision-ready insights for defense users
• Build scalable REST, GraphQL, and gRPC APIs and containerized services
• Connect Python tooling to the core simulation runtime and downstream analysis tools
• Gather requirements from government stakeholders, domain experts, and analysts
• Distill requirements into clear software designs
• Apply code review, testing, continuous integration, release management, and build-system practices
• Develop backend infrastructure interfacing with agentic AI and machine-learning pipelines
• Provide architectural guidance, technical scoping, design documentation, technical grooming, design spikes, RFCs, and mentorship at staff level

Skills

Python Development

Scalable API Development

Docker Containerization

Cloud Distributed Systems

SDLC Practices

Machine Learning Tools

Code Review & Testing

CI/CD

Tools

AWS

GCP

Azure

Agentic AI Frameworks

Job description

• Design and implement backend services and APIs orchestrating mission- and campaign-level simulation runs
• Collect simulation outputs and expose results to analysts and government stakeholders
• Build scenario-generation, operational and mission-planning workflows
• Build Monte Carlo-based sensitivity-analysis services
• Build distributed, cloud-scale infrastructure across developer workstations, on-premises infrastructure, and cloud compute
• Preserve simulation reproducibility and model provenance
• Build data ingestion, normalization, and analysis pipelines producing decision-ready insights for defense users
• Build scalable REST, GraphQL, and gRPC APIs and containerized services
• Connect Python tooling to the core simulation runtime and downstream analysis tools
• Gather requirements from government stakeholders, domain experts, and analysts
• Distill requirements into clear software designs
• Apply code review, testing, continuous integration, release management, and build-system practices
• Develop backend infrastructure interfacing with agentic AI and machine-learning pipelines
• Provide architectural guidance, technical scoping, design documentation, technical grooming, design spikes, RFCs, and mentorship at staff level

Requirements

• 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
• Staff level expectation: 7+ years of experience
• Preferred: familiarity with agentic AI frameworks and solutions
• Preferred: familiarity with code analysis/static analysis
• Preferred: experience with AWS, GCP, or Azure cloud-based distributed systems
• Preferred: active U.S. security clearance (Secret, Top Secret, or SCI/SAP)
• Preferred: direct experience developing AFSIM plugins, framework extensions, event infrastructure, or custom platform types
• Preferred: familiarity with HLA, DIS, OneSAF, JSAF, NGTS, STK, or other constructive and distributed simulation environments
• Preferred: experience supporting Air Force, Space Force, joint, or broader DoD acquisition and mission-analysis programs
• Preferred: experience developing models for sensors, weapons, electronic warfare, jamming, communications, logistics, or command and control
• U.S. Citizenship may be required for certain project assignments involving security clearance

Core Competencies

Demonstrates expertise in designing and implementing scalable backend services and APIs, with a strong focus on Python development and robust software delivery practices. Proficient in building cloud-scale infrastructure and data pipelines for defense applications, while ensuring simulation reproducibility and model provenance.

Highest-signal resume keywords

• Python Development
• Scalable API Development
• Docker Containerization
• Cloud-Based Distributed Systems
• Software Development Life Cycle (SDLC) Practices

Hard Skills

• Backend Service Design
• API Development (REST, GraphQL, gRPC)
• Data Ingestion and Normalization
• Monte Carlo Sensitivity Analysis
• Machine Learning Tools and Frameworks
• Code Review and Testing
• Continuous Integration
• Release Management
• Build Systems
• Simulation Environment Familiarity

Soft Skills

• Requirement Gathering
• Stakeholder Communication
• Mentorship

Certifications & Qualifications

• U.S. Top Secret Security Clearance

Industry Keywords

• Defense
• Simulation
• DoD Acquisition
• Mission Analysis
• HLA
• DIS
• OneSAF
• JSAF
• NGTS
• STK

Tools & Technologies

• Docker
• AWS
• GCP
• Azure
• Agentic AI Frameworks