Senior Staff Software Engineer, Autonomous Pilot Integration (R5193)

Job Description

Job Description

Founded in 2015, 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 and V-BAT and X-BAT aircraft. 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 Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

The Autonomous Pilot Integration team builds autonomy solutions for a wide range of CONOPs and mission sets. We combine capabilities from the Autonomy Capabilities team (motion planning, tactics), the Perception team (e.g., track fusion), and the HivemindSDK to develop the autonomy software that runs on an unmanned platform — air, maritime, space, or effects/expendables, depending on the program — then integrate, validate, and field it on the real hardware. In this role, you'll write new autonomy code — such as mission behaviors, platform-specific control, multi-agent coordination, contingencies, and executive autonomy — and own it end-to-end from software-in-the-loop, to hardware-in-the-loop, to vehicle-in-the-loop, to live test exercise. You'll partner closely with the Autonomy Capabilities and Perception teams, feature crews, and external platform integrators (vehicle/autopilot control vendors, C2 providers). It's a hands-on role for engineers who like seeing their code operate in the real world — whether that's flying, sailing, orbiting, or downrange — and want to be there when it does. 

At this level, you'll own the technical direction across multiple programs — driving the autonomy reference implementation and common patterns that portfolios adopt, anticipating where the autonomy stack needs to evolve, adapting as programs and priorities shift, and aligning with engineering leadership early. You'll serve as the subject-matter expert other teams seek out on hard, ambiguous problems in unknown solution spaces; mentor senior engineers and other team leads; drive cross-team improvements in rigor and process; and represent the team to engineering leadership, customer/program offices, and standards bodies. 

Shield AI is committed to developing cutting-edge autonomy for unmanned platforms across every operating domain — air, maritime, space, and effects/expendables — in service of the U.S. Department of Defense and our international defense customers. Our Autonomous Pilot Integration engineers bridge the gap between R&D and deployment, ensuring autonomous systems function reliably and effectively wherever and whenever they're needed most. 

• Develop & Field Autonomy — Develop & integrate autonomy software solutions onto unmanned platforms (air, maritime, space, or effects/expendables), including payload computer bring-up, container-based deployment (e.g., k3s/k3d), and configuration across onboard compute, sensors, and command-and-control interfaces — and own the technical direction across a set of related programs, driving the autonomy reference implementation and common patterns that keep delivery coherent across portfolios. 

• Technical Strategy & Leadership — Set the technical direction across multiple programs; drive the autonomy reference implementation and common patterns that portfolios adopt; anticipate where the stack needs to go and adapt as priorities shift; align with engineering leadership early and maintain outward status; serve as the subject-matter expert that the broader org reaches for when hard, ambiguous problems in unknown solution spaces land on the team. 
• Collaboration & Cross-Engineering Influence — Build effective working relationships across engineering; represent the team to engineering leadership, customer/program offices, standards bodies, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers); shape architecture decisions beyond the team. 
• Mentorship & Growth — Mentor senior engineers and other team leads; provide cross-functional mentorship to engineers in adjacent departments; help shape the leveling and career bar for the team and the broader engineering organization. 
• Design & Documentation — Drive cross-functional design reviews, architecture documents, and post-mortems across many teams; publish content that informs decisions beyond the team; set the rigor and process bar for the broader engineering org. 
• Pre-deployment Preparation — Own the build, configuration, and validation process for mission-ready systems; coordinate hardware/software compatibility, mission readiness, and release cadence with capability and feature teams. 
• On-site Test & Mission Support — Travel to test sites and support live mission operations (flight tests, range exercises, on-water trials, integration events), including safety checks, system bring-up, and troubleshooting under time-critical constraints. 
• Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy stacks, payload computers, and embedded systems in lab and field environments — including memory, CPU, and timing profiling under operationally-representative loads. 
• Mission Data & Debrief Support — Capture mission and test data, reproduce issues in simulation, and partner with autonomy capability owners to drive fixes back into the next build. 
• Continuous Improvement — Build tools and processes to improve integration timelines, test/mission reliability, and team efficiency across deployment cycles. 
• C2 Interoperability & Standards — Set the strategy for C2 interoperability across our portfolio; shape interface evolution with internal and external stakeholders; own implementation and compliance against command-and-control standards (e.g., A-GRA, UCI, OMS). 
• Hiring — Define the skills bar and hiring strategy for senior roles in your area; partner with managers on long-term staffing plans; assess candidates accurately and onboard new senior engineers. 
• Travel Requirement – Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test events). 

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience 
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience. 
• Proficiency in C++, with experience developing or integrating real-time or latency-sensitive systems. 
• Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics. 
• Familiarity with middleware, pub-sub, or IPC frameworks used in autonomy or robotics systems (e.g., DDS, message buses). 
• Hands-on experience supporting demos, exercises, or field/mission tests for unmanned or autonomous systems. 
• Experience with autonomy simulation environments for testing and validation. 
• Demonstrated experience leading multiple teams or driving cross-program technical initiatives from concept through fielded delivery. 
• Track record as the subject-matter expert sought across engineering on hard, ambiguous problems in unknown solution spaces in your discipline. 
• Track record of setting forward-looking technical strategy and adjusting course as programs and priorities evolve. 
• Track record of mentoring senior engineers and team leads, and shaping the career bar for the discipline. 
• Experience shaping architecture decisions, interface contracts, and standards across multiple teams. 
• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance across the full stack. 
• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment. 
• Ability to obtain a SECRET clearance. 

• Direct experience supporting unmanned systems (air, maritime, space, ground, or effects/expendables) or similar field test campaigns. 
• Proficiency in Python for scripting, automation, and analysis. 
• Experience leading multiple programs or driving cross-program technical initiatives in an unmanned systems context. 
• Experience interfacing with customers and external stakeholders, representing the company in technical engagements, briefing senior leadership, and presenting to non-technical audiences. 
• Track record of improvements that span the broader engineering organization (process, architecture, technical bar, or platform-wide tooling). 
• Familiarity with autonomy stacks, motion planning, or vehicle-control integration. 
• Competence in vehicle electronics bring-up (avionics, spacecraft buses, or vessel control), payload computer integration, or hardware-in-the-loop debugging. 
• Experience with container orchestration (e.g., k3s, k3d, Docker) on embedded or payload compute. 
• Familiarity with platform control / autopilot stacks (e.g., PX4, ArduPilot, spacecraft flight software, vessel autopilots). 
• Proficiency in developing automation tools for system testing, logging, and data parsing. 
• Build-system experience (e.g., Conan, CMake) and CI/CD pipeline familiarity. 
• Comfortable interfacing with DoD stakeholders during field events or technical reviews. 
• Experience with C2 standards such as A-GRA, UCI, or OMS. 
• Familiarity with government-furnished simulation environments (e.g., AFSIM, NGTS) is a plus. 

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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.

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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. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.