Design and implement high-performance middleware, runtime services, tooling, and foundational software for Shield AI’s EdgeOS and Hivemind autonomy systems. Develop across Linux, real-time operating systems, and resource-constrained embedded platforms. Contribute to interface definition languages, debugging and observability tools, automated testing, documentation, architecture, code reviews, technical guidance, and mentorship while collaborating with autonomy, systems, simulation, and test engineering teams.
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.
Shield AI is seeking a Senior Engineer to help design and develop the middleware framework upon which Shield AI autonomy is developed. As part of the Hivemind Foundations team, you’ll focus on building the high-performant, reliable, and robust foundational layer of the Hivemind SDK, EdgeOS. The Hivemind Foundations team ensures that autonomous systems have the functionality required to deploy to platforms operating in some of the most restrictive and demanding environments around the world. They also create the tools that enable autonomy engineers develop, understand, debug, and rapidly iterate on complex autonomous systems.
What you'll do:
- Own the architecture and implementation of features critical to EdgeOS and EdgeOS RT middleware.
- Develop runtime services and abstractions that operate across Linux, real-time operating system, and resource-constrained computing platforms.
- Design and develop the tooling used to evaluate, observe, and debug autonomous systems.
- Contribute to and extend EdgeOS Language, Hivemind’s interface definition language, which defines how data is represented within autonomous systems, between agents, and with third-party systems.
- Collaborate closely with autonomy, systems, simulation, and test engineers to deliver capabilities from initial design to integration.
- Raise the engineering bar though design and code reviews, technical guidance, documentation, and mentorship.
Required qualifications:
- Bachelor’s degree in Computer Science, Electrical Engineering, or a related field.
- Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years with a Master’s; or 4 years with a PhD; or equivalent work experience.
- Strong proficiency in C++11 or newer in a production environment.
- Experience designing, developing, and debugging multithreaded systems.
- Experience developing software for real time operating systems and embedded platforms.
- Strong understanding of systems programming concepts, including concurrency, memory management, resource constraints, and performance optimization.
- Experience writing automated tests and clear technical documentation.
Preferred qualifications:
- Experience with C++17 or newer standards.
- Experience writing MISRA C++ or comparable coding standards for safety-critical or airborne systems.
- Experience with systems engineering design principles and requirements.
- Experience software assurance frameworks such as DO-178C.
- Familiarity with ROS2 or similar robotics frameworks.
- Experience with interface definition languages, serialization systems, or code-generation tooling.
- Knowledge of CMake and Nix build systems.
- Experience profiling and debugging complex software across multiple hardware and operating-system environments.
#LI-KC3
#LC
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
Lead architecture, development, integration, and testing of safety-critical C++ Run-Time Assurance software for autonomous aircraft. Drive rigorous coding, assurance, certification, documentation, and testing practices; integrate software with autonomy and middleware systems; ensure fail-safe behavior across platforms; mentor engineers; and provide technical leadership for reliable, certifiable flight software.
Top Skills:
C++Ci/CdDo-178CGitJsf Av C++LinuxMil-Hdbk-516Misra C++Test-Driven Development
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software • Defense Technology
Develop and maintain C++ and Python simulation adapters, plugins, interfaces, and reusable framework components. Support migration from HMSSimBlocks to HMSF, integrate simulation backends, maintain CIGI and DDS interfaces, troubleshoot autonomy integration issues, and create tests and documentation. Collaborate with senior engineers on code reviews, debugging, design discussions, and integration support across simulation and autonomy teams.
Top Skills:
AechelonAfsimAPIsBazelC++CigiCmakeCommon Scenario Format (Csf)CtestDdsDockerGazeboGitGoogletestGrpcHivemind Simulation Framework (Hmsf)HmssimblocksLinuxMakeMatlabNgtsPodmanPytestPythonRosRos 2SimulinkTcpUdpUnityUnreal EngineZeromq
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software • Defense Technology
Develop and maintain C++ and Python simulation adapters, plugins, interfaces, and reusable components. Support migration from HMSSimBlocks to HMSF, integrate simulation backends, maintain CIGI and DDS communications, diagnose distributed-system issues, and create tests and documentation. Collaborate with simulation, autonomy, and integration teams on code reviews, debugging, and framework improvements.
Top Skills:
AechelonAfsimBazelC++CigiCmakeCommon Scenario Format (Csf)CtestDdsDisDockerGazeboGitGoogletestGrpcHivemind SdkHivemind Simulation Framework (Hmsf)HlaHmssimblocksLinuxMakeMatlabNgtsPodmanPytestPythonRosRos 2SimulinkTcpUdpUnityUnreal EngineZeromq
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
