Build and lead simulation platform infrastructure for autonomous aircraft systems. Responsibilities include integrating and developing simulators, creating scalable Monte Carlo experimentation capabilities, implementing multithreaded and multiprocess real-time simulations, validating physics models, partnering with autonomy and GNC teams, and guiding architecture, design reviews, and engineering mentorship.
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
The Hivemind Simulation team provides the simulation capabilities that power the AI Factory’s training and evaluation for the next generation autonomous AI pilots. The Simulation Platform team builds the simulation framework and foundational infrastructure that allows engineers to bring together simulators, scale experiments, and confidently evaluate autonomy before flight. The team’s work enables simulation applications to build on a shared, performant, and extensible foundation. Our guiding principle is simple: autonomy should not know it is in a simulation.
As a Staff Software Engineer on the Simulation Platform team, you will shape how autonomous pilots are tested by building and integrating simulators and developing Monte Carlo infrastructure. Drawing on experience building and running real-time aircraft simulations, you will enable teams to evaluate autonomy, guidance, navigation, and control (GNC), and runtime assurance (RTA) systems at scale. This individual contributor role includes driving technical direction and mentoring engineers.
What you'll do:
- Grow the simulation framework’s ecosystem by integrating existing simulators and established standards, and by build new ones where needs are identified.
- Build reusable Monte Carlo infrastructure for parameterization, execution, reproducibility, and collection of results across large simulation campaigns.
- Develop multithreaded and multi-process simulation capabilities, addressing synchronization, timing, state exchange, and performance.
- Partner with autonomy, GNC, and RTA engineers as well as operators in the field to translate evaluation needs into simulation interfaces and infrastructure.
- Support platform specific performance validation using physics models (e.g, 6DoF, 3DoF, etc.).
- Set technical direction, lead design reviews, and mentor engineers in simulation architecture and production software development.
Required qualifications:
- Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years with a Master’s degree; or 7 years with a PhD; or equivalent work experience.
- Strong proficiency in C++, with demonstrated experience designing, implementing, and maintaining production performance-critical software.
- Demonstrated experience building and running multithreaded/multiprocess real-time simulations involving aircraft dynamics.
- Experience both developing Monte Carlo infrastructure and using it to design, execute, and analyze simulation campaigns.
- Demonstrated ability to drive technical decisions, mentor engineers, and collaborate across software and domain engineering teams.
- Experience developing software/simulation under a defined V&V lifecycle
Preferred qualifications:
- Experience supporting airworthiness certification efforts, including developing simulation evidence for verification, validation, and safety assessment (e.g., DO-178C, MIL-HDBK-516C).
- Strong Python skills for simulation tooling, experiment automation, and analysis.
- Experience with distributed simulation and model interoperability standards such as HLA, DIS, and FMI/FMU.
- Experience with industry-standard simulation tools such as JSBSim, FlightGear, X-Plane, Gazebo, Isaac Sim, or Simulink, or equivalent environments.
- Experience with closed-loop autonomy simulation, including sensor inputs and interfaces between autonomy and the simulated environment.
- Experience with uncertainty modeling, statistical analysis, and scenario coverage for Monte Carlo evaluation.
- Testing / Operating Safety Critical Software (e.g., DO-178C)
#LI-JS3
#LD
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
###
Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
Similar Jobs at Shield AI
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software • Defense Technology
Supports the design, integration, prototyping, testing, and release of mechanical systems for autonomous aircraft. Responsibilities include CAD modeling, drawings, bills of materials, tolerance analysis, engineering calculations, preliminary FEA, component selection, prototype testing, aircraft integration, troubleshooting, and root-cause analysis. Collaborates with multidisciplinary engineering, manufacturing, and test teams while completing defined tasks under guidance.
Top Skills:
3D CadFinite Element AnalysisFmeaGd&TMatlabMil-Std-810NxPythonRtca Do-160
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software • Defense Technology
Develop and maintain automated test frameworks, CI/CD pipelines, and validation infrastructure for distributed autonomy software and hardware systems. Build Python tooling, UI and API test automation, simulators, test harnesses, and hardware-in-the-loop solutions. Analyze failures, improve coverage and observability, and collaborate with engineering teams on verification strategies for safety-critical aerospace software. The role also evaluates AI-assisted development tools for test generation, debugging, log analysis, and workflow automation.
Top Skills:
APIsCC++Ci/CdClaude CodeCodexConanGitlab CiGoHardware-In-The-Loop (Hil)Large Language Models (Llms)LinuxNixPipPoetryPythonSetuptoolsShell ScriptingTypescriptYaml
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software • Defense Technology
Leads a distributed infrastructure team and owns strategy, architecture, operations, modernization, and lifecycle management across hybrid enterprise, data center, lab, manufacturing, and engineering environments. Oversees compute, storage, virtualization, servers, backup, disaster recovery, PLM infrastructure, vendors, budgets, incidents, security, compliance, and infrastructure readiness. Partners with cloud, network, cybersecurity, facilities, and application teams while developing technical talent and ensuring reliable, scalable services.
Top Skills:
Active DirectoryAnsibleBashCmmcCohesityDcimEntra IdHyper-VInfrastructure As CodeItarKvmLinuxNetappNist 800-171PowershellPythonTeamcenterTerraformVMwareWindows
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
