Manager of Engineering - Autonomous Pilot Integration - Emerging Domains (R5176)

United States / San Diego, California / Washington, DC / Boston, MA

Hivemind Solutions Division – Flight System Integration /

Full Time Employee /

On-site

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 www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.

Job Description:

The Autonomous Pilot Integration team for emerging domains builds autonomy solutions for new platforms and mission profiles outside Shield AI's established portfolios — including space (satellites, missile defense), maritime (USV and UUV integration), and contested logistics (unmanned helicopters and related autonomous resupply platforms). The team takes on short-term R&D and integration efforts — often standing up the first autonomy on a brand-new platform or for a brand-new mission — with the intent that successful efforts grow into larger, multi-year programs. We combine capabilities from the Autonomy Capabilities team (motion planning, tactics), the Perception team (e.g., ViDAR, ATR), and the HivemindSDK — selectively leveraging existing Shield AI autonomy solutions where they apply — to develop autonomy that runs on these new platforms. Our engineers 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.

In this role, you'll lead a team of autonomy engineers tackling autonomy across Shield AI's emerging-domain efforts — owning their delivery, their growth, and the technical health of your area. A core part of the job is growing the team: hiring strong engineers, mentoring them through hard technical work, and shaping their career development. You'll stay technically active — writing code where it best serves the team, staying close to the integration work, making sound technical decisions, and leading them through the design, development, and delivery of efforts that may shift in shape, scope, and timeline. This role demands a problem solver who thrives in the unknown — you'll be standing up first autonomy on platforms that often don't have an established autopilot interface, mission autonomy, or operator base yet, and you'll be comfortable with priorities and deadlines that shift as programs mature. You'll partner closely with the platform teams that build each new piece of hardware (spacecraft, vessel, helicopter, etc.), the Autonomy Capabilities, Perception, and GCS teams, and customer/program offices on each effort. Success here means turning short-term R&D and integration efforts into longer-term programs that scale — with the growth opportunity, if desired, to lead the new portfolios that emerge from this work as they mature and graduate from emerging domains.

What you'll do:

Lead the Team — Manage an engineering team (typically 5–10 engineers spanning multiple emerging-domain efforts); own performance, growth, leveling, and delivery; run 1:1s, performance reviews, and team rituals.
Grow the Team via Hiring — Drive hiring for your area: identify the skills you need, partner with recruiting, run interviews, set the bar, and personally close strong candidates.
Grow Engineers Technically — Mentor engineers through hard problems; create stretch opportunities; give direct, actionable technical feedback; help engineers level up in both skill and impact.
Stand Up New Programs — Stand up autonomy on new platforms and missions — often as the first autonomy engineering presence on the program. Define what the autonomy stack looks like, decide what to build versus what to leverage from existing Shield AI capabilities, and set the technical direction for the effort.
Navigate Ambiguity & Shifting Priorities — Operate effectively in an environment where program shape, scope, and timeline often shift. Make sound technical and staffing decisions with incomplete information, communicate changes clearly to your team and stakeholders, and protect engineering velocity through churn.
Develop & Field Autonomy — Develop & integrate autonomy software solutions onto emerging-domain platforms — satellites, USVs/UUVs, unmanned helicopters, and similar — including platform and autopilot integration, payload and sensor integration, mission behaviors, and validation across software-in-the-loop, hardware-in-the-loop, vehicle-in-the-loop, and live test events. Lead a small team through the design, development, and delivery of each effort.
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.
Hands-on Technical Contribution — Stay active in the code; contribute directly where it serves the team — prototyping new capabilities, taking on deep technical analysis of hard problems, or absorbing critical work during demo crunch. This is a manager role, not a managing-only role.
Platform Team Partnerships — Build strong partnerships with each platform team that owns the underlying hardware (spacecraft, vessel, rotorcraft, or other autonomous system) — coordinating on platform changes, autopilot or control-interface evolution, sensor integration, and release planning. Relationships and tight coordination with these teams are critical for success on each new program.
Collaboration Across Teams & Partners — Act as a primary technical interface with the Autonomy Capabilities, Perception, and GCS teams, feature crews, and customer/program offices (U.S. and international); author and negotiate ICDs and interface contracts rather than just consume them.
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 platform teams.
On-site Test & Mission Support — Travel to test sites, customer exercises, and demonstrations to support live mission operations — flight tests, range exercises, on-water trials, satellite ground tests, and similar — 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 compliance against common message and open-systems standards relevant to each program (e.g., UCI, OMS, STANAG 4586 for aerial systems, and program-appropriate standards for maritime and space).
Grow R&D into Programs — Work with leadership and customers to evolve successful short-term R&D efforts into larger, longer-term programs; help shape pursuit strategy and scope as programs mature.
Travel Requirement – Members of this team typically travel around 20-30% of the year (to different office locations, customer sites, test events, and integration 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.
2+ years of direct people-management experience (running 1:1s, performance reviews, hiring decisions, growth planning).
Demonstrated experience building or growing an engineering team — including interviewing, hiring, and onboarding new engineers.
Track record of mentoring engineers and growing their technical skill and career trajectory.
Demonstrated experience leading a small technical team or owning a major capability from design through field delivery.
Demonstrated ability to thrive in ambiguity — standing up new efforts with incomplete requirements, making sound decisions with limited information, and adapting to shifting deadlines and priorities.
Experience standing up autonomy on a new platform or for a new mission type (R&D, prototype, or early-stage integration efforts).
Experience authoring or negotiating interface contracts / ICDs with internal or external stakeholders.
Direct experience with autonomous unmanned systems — air, maritime (USV/UUV), space, ground, or rotorcraft.
Strong 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.
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:

Experience across multiple unmanned-system domains (e.g., air + maritime, air + space, or similar).
Direct experience with autonomy for space platforms (satellites, missile defense), maritime systems (USV/UUV), or rotorcraft.
Proficiency in Python for scripting, automation, and analysis.
Experience leading a feature crew, sub-program, or small team in an unmanned systems context.
Experience growing engineers from mid-level into senior IC, or supporting promotion decisions through a leveling framework.
Experience taking R&D or prototype efforts into larger production or fielded programs.
Experience integrating autonomy with custom or in-house autopilot/control stacks at the platform integration level.
Experience with payload and sensor integration on novel platforms (e.g., EO/IR, ViDAR, maritime sensors, space payloads).
Experience owning customer- or partner-facing technical relationships (e.g., platform 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 avionics/payload-computer integration, hardware-in-the-loop debugging, or comparable bring-up on novel platforms.
Experience developing for or deploying onto ARM-based systems (e.g., embedded payload computers).
Experience with containerization (e.g., Docker) on embedded or payload compute.
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 supporting international defense customer programs (FMS or direct commercial sales).
Experience with common message and open-systems standards such as UCI, OMS, STANAG 4586, or domain-equivalents for maritime and space.

$220,000 - $330,000 a year

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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.

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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