Shield AI is seeking a Staff Engineer to help design, develop, and integrate a safety critical Run-Time Assurance (RTA) product. The Hivemind Foundations team is responsible for a suite of core products and capabilities that brings resilient autonomy and intelligence to aircraft and other platforms operating in complex environments. The RTA product that the Foundations team develops is a real-time safety capability that helps keep autonomy safe, predictable, and effective at the edge.
As a senior member of the Hivemind Foundations team, you will lead applied trajectory prediction and aircraft-response modeling for the RTA. You will work at the boundary between safety logic, vehicle state, and autopilot or flight-control APIs, turning aircraft performance data, command-response assumptions, and test evidence into predictive models that guide safe recovery behavior. You will evolve Trajectory Prediction Algorithm (TPA) models, validate them with Python, simulation, HIL, and flight-test data, and partner with C/C++ engineers to deliver reliable software that can fly, including support for X-BAT, Shield AI's flagship Group 5 Collaborative Combat Aircraft (CCA) UAV.
What you'll do:
- Lead development, tuning, and validation of TPA and recovery-behavior models using aircraft performance data, command-response assumptions, 3DOF/6DOF flyout concepts, wind effects, uncertainty bounds, and maneuver constraints.
- Build Python-based analysis, simulation, HIL, and flight-test workflows to compare predicted versus observed aircraft behavior, identify model gaps, tune parameters, and maintain regression datasets.
- Integrate and evaluate trajectory-prediction behavior through off-the-shelf or custom autopilot interfaces, including command modes, vehicle-state inputs, latency, mode transitions, control limits, and telemetry analysis.
- Support hardware integration and flight-test campaigns across relevant platforms; also help evolve trajectory-prediction and safety behaviors from single-aircraft use cases toward multi-agent collaborative CONOPS. Produce algorithm handoff artifacts and contribute scoped C/C++ implementation, testing, and debugging as needed.
Required qualifications:
- Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years with a Master’s degree; or 4 years with a PhD; or equivalent work experience.
- Deep experience in trajectory prediction, aircraft-response modeling, aerospace simulation, robotics, applied autonomy, or GNC-adjacent domains, including 3DOF and/or 6DOF aircraft modeling concepts.
- Expert-level Python skills for algorithm development, numerical analysis, data processing, plotting, tuning workflows, and test automation.
- Working proficiency in C or C++, with the ability to read production code, debug algorithm behavior, write tests, make scoped implementation changes, and guide software engineers through algorithm intent.
- Demonstrated experience interfacing guidance, trajectory, or safety-critical algorithms with off-the-shelf or custom autopilots and validating behavior through simulation, HIL, flight hardware, or flight-test data.
- Ability to document model assumptions, handoff artifacts, and validation evidence while leading technical coordination across algorithms, software, systems, test, and platform teams.
Preferred qualifications:
- Experience tuning trajectory prediction, flyout, or vehicle-response models from simulation, HIL, or flight-test telemetry.
- Experience implementing or porting algorithms from Python, MATLAB/Simulink, or prototype models into C or C++ production software.
- Experience with Monte Carlo testing, scenario-based regression, validation metrics, envelope expansion, test-card planning, or flight-test safety reviews.
- Familiarity with high-reliability or safety-critical development practices, such as static analysis, coding standards, traceability, requirements-based testing, and verification evidence.
- Experience with CMake, Conan, Linux, CI/CD, embedded software workflows, or production software integration.
Skills Required
- Bachelor's degree with at least 7 years of related experience, Master's degree with at least 6 years, PhD with at least 4 years, or equivalent work experience
- Deep experience in trajectory prediction, aircraft-response modeling, aerospace simulation, robotics, applied autonomy, or GNC-adjacent domains
- Experience with 3DOF and/or 6DOF aircraft modeling concepts
- Expert-level Python skills for algorithm development, numerical analysis, data processing, plotting, tuning workflows, and test automation
- Working proficiency in C or C++ for reading production code, debugging, testing, scoped implementation, and guiding software engineers
- Experience interfacing guidance, trajectory, or safety-critical algorithms with autopilots
- Validation experience using simulation, hardware-in-the-loop, flight hardware, or flight-test data
- Ability to document model assumptions, handoff artifacts, and validation evidence while coordinating across technical teams
- Experience tuning trajectory prediction, flyout, or vehicle-response models from simulation, HIL, or flight-test telemetry
- Experience porting algorithms from Python, MATLAB/Simulink, or prototypes into C or C++ production software
- Experience with Monte Carlo testing, scenario-based regression, validation metrics, envelope expansion, test-card planning, or flight-test safety reviews
- Familiarity with safety-critical development practices, static analysis, coding standards, traceability, requirements-based testing, and verification evidence
- Experience with CMake, Conan, Linux, CI/CD, embedded software workflows, or production software integration
What the Team is Saying
What We Do
At Shield AI, you won't wait years to see your work reach the field. You'll build hardware and software that operates in the real world right now, in the hands of the people who depend on it. Hivemind, our AI pilot, has been flying since 2018. It has flown more than 30 platforms, including an F-16, and it now sits under a U.S. Air Force production contract for Collaborative Combat Aircraft. When you write code or shape a system here, you contribute to technology with a proven flight record and a clear production future. V-BAT flies intelligence, surveillance, and reconnaissance missions with an operational record that stretches from Ukraine to the Indo-Pacific. It delivers eyes where they matter most, in the most demanding conditions on earth. The teams behind it watch their work get tested where the stakes are real. X-BAT takes its first flight this year. It's an AI-piloted fighter that needs no runway, built to operate where traditional aircraft can't. Join now and you help shape a program at its earliest, most formative stage. That's the kind of ground-floor work that defines a career. Do the most impactful work of your life, on problems that matter. Autonomy at this level asks a lot of you. You'll take on problems in perception, planning, and control that few teams anywhere are equipped to solve. You'll work across disciplines, from aerospace and robotics to machine learning and systems engineering, alongside people who hold themselves to an exacting standard and expect the same from you. Our mission is clear: protect service members and civilians with intelligent systems. That purpose runs through every decision, every design review, and every deployment. It's why the work here carries a weight you can feel. Ready to join our mission? Explore our open roles and find where you fit.
Why Work With Us
Founded in 2015 by a former Navy SEAL, Shield AI builds AI pilots and uncrewed aircraft. Veterans aren't an afterthought here, they're at every level. It's why the work carries weight: AI pilots and uncrewed aircraft flying real missions, from Ukraine to the Indo-Pacific, protecting service members and civilians.
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