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How much do sub pilot jobs pay per year?

As of Sep 9, 2026, the average yearly pay for sub pilot in the United States is $130,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $155,000.00 per year, depending on experience, location, and employer.

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Infographic showing various Sub Pilot job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 85% Full Time, 9% Part Time, 2% Contract, and 2% Nights. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $130,916 per year, or $62.9 per hour.

Staff Software Engineer, Autonomous Pilot Integration (R5208)

Boston, MA • On-site

Shield AI
Software Development • 11 - 50 employees
Learn more about Shield AIexternal

Full-time

Re-posted 4 days ago

Job description

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 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 also serve as a technical leader within the team - leading a small feature crew or sub-program through design, integration, and delivery, mentoring mid-level engineers, and representing the team directly to capability teams and external partners. 

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. 

What You'll Do:

  • 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 lead a small team through the design, development, and delivery of a major capability or sub-program. 

  • Technical Leadership - Lead a small feature crew or sub-program; set technical direction, break down work, unblock the team, and report progress to leadership and stakeholders. 

  • Collaboration Across Teams - Act as a primary technical interface with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers); author and negotiate ICDs and interface contracts rather than just consume them 

  • Mentorship & Growth - Mentor mid-level engineers on the team; partner with managers on onboarding, leveling, and growth planning. Formally onboard senior new hires. 

  • Design & Documentation - Drive design reviews, ICDs, and post-mortems for your area; push the team toward higher rigor and close process gaps that span teams. 

  • 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 - Own the interface contracts with C2 providers and drive standards compliance for your area, including implementation and validation against command-and-control standards (e.g., A-GRA, UCI, OMS). 

  • Hiring - Interview candidates, help define the skills bar for open roles in your area, and onboard new engineers into your sub-program. 

  • Travel Requirement - Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test events). 

Required Qualifications:

  • BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience 

  • Typically requires a minimum of 7 years of related experience with a Bachelor's degree; or 5 years and a Master's degree; or 4 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 a small technical team or owning a major capability from design through field delivery. 

  • Track record of mentoring engineers and growing technical talent. 

  • Experience authoring or negotiating interface contracts / ICDs with internal or external stakeholders. 

  • 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. 

Preferred Qualifications:

  • 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 a feature crew, sub-program, or small team in an unmanned systems context. 

  • Experience owning customer- or partner-facing technical relationships (e.g., autopilot vendors, C2 providers, government program offices). 

  • Track record of cross-team improvements (process, rigor, documentation, or developer experience). 

  • 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. 

$195,200 - $292,800 a year
#LI-ED1
#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.
 
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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.
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