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Autonomous Jobs in Boston, MA (NOW HIRING)

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Autonomous information

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$34.8K

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How much do autonomous jobs pay per year?

As of Aug 20, 2026, the average yearly pay for autonomous in Boston, MA is $53,376.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,500.00 and $59,800.00 per year, depending on experience, location, and employer.

What is an autonomous job?

Autonomous jobs refer to roles or tasks that are performed independently, often with minimal supervision or direction. In the context of technology, autonomous jobs usually involve the use of artificial intelligence or robotics to carry out work without constant human intervention. These positions might include operating or overseeing autonomous vehicles, managing automated systems, or developing technologies that support automation. The goal is to improve efficiency, safety, and productivity by reducing the need for manual oversight. Careers in this field can span across industries such as transportation, manufacturing, logistics, and IT.

What are the key skills and qualifications needed to thrive as an autonomous vehicle engineer?

To thrive as an Autonomous Vehicle Engineer, you need solid expertise in robotics, computer vision, machine learning, and a background in computer science or engineering. Familiarity with programming languages like Python and C++, as well as experience with ROS (Robot Operating System) and simulation tools, is typically required. Strong problem-solving skills, attention to detail, and effective teamwork set standout professionals apart. These abilities are crucial for developing safe, reliable autonomous systems that perform well in complex, real-world environments.

How does an autonomous systems engineer typically collaborate with cross-functional teams during a project?

Autonomous Systems Engineers work closely with software developers, hardware engineers, data scientists, and project managers to design, test, and deploy autonomous technologies. Collaboration often involves regular team meetings, sharing technical documentation, and joint problem-solving sessions to ensure seamless integration of system components. Engineers may also coordinate with testing teams to validate system performance and safety, making effective communication and teamwork essential skills in this role.
Infographic showing various Autonomous job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $53,376 per year, or $25.7 per hour.

Manager of Engineering - Autonomous Pilot Integration (R5153)

Shield AI

Boston, MA • On-site

Full-time

Re-posted 10 days ago


Job description

Job Summary:
Shield AI is a venture-backed defense-tech company focused on protecting service members and civilians with intelligent systems. The Manager of Engineering - Autonomous Pilot Integration will lead a team of engineers to develop and integrate autonomy software solutions for defense applications, ensuring reliable functionality in various environments.
Responsibilities:
• Lead the Team — Manage a small-to-mid-sized engineering team (typically 3–8 engineers); 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.
• Develop & Field Autonomy — Develop & integrate autonomy software solutions onto launched effects platforms, including payload computer bring-up, autopilot integration (e.g., PX4, ArduPilot), multi-agent coordination, and fleet-scale deployment to disconnected or air-gapped environments — and lead a small team through the design, development, and delivery of a major capability or 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 & Partners — Act as a primary technical interface with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, autopilot vendors (e.g., PX4, ArduPilot), C2 providers, and customer/contractor partners (including embedded contractor engineers and U.S. or international government program offices); 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 and fleet-scale deployments (often 50–150+ units in disconnected environments); coordinate hardware/software compatibility, mission readiness, and Capability Release (CR) cadence with capability and feature teams.
• On-site Test & Mission Support — Travel to test sites and customer exercises to support live mission operations (flight tests, range exercises, multi-agent live events, customer demonstrations), 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 (e.g., UCI, OMS, MOSA, WOSA, TAK/CoT).
• Travel Requirement – Members of this team typically travel around 20-30% of the year (to different office locations, customer sites, range exercises, and integration events).
Qualifications:
Required:
• 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.
• Experience authoring or negotiating interface contracts / ICDs with internal or external stakeholders.
• Direct experience with launched effects, loitering munitions, expendable autonomous systems, or comparable small unmanned platforms.
• Experience with multi-agent, swarm, or fleet-scale autonomy.
• 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 live exercises, customer demonstrations, or operational test events for launched effects or similar small unmanned 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:
• Direct experience with PX4 and/or ArduPilot at the platform integration level.
• Experience using and developing on QGroundControl (QGC) or other Qt-based ground control stations.
• 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 with air-gapped, disconnected, or otherwise constrained deployment of autonomous systems at fleet scale.
• Familiarity with tactical edge C2 (e.g., TAK, CoT) and ground operator workflows.
• Experience working with embedded contractor engineers, FFRDC partners, or customer-funded staff augmentation models.
• Experience supporting international defense customer programs (FMS or direct commercial sales).
• 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 avionics bring-up, payload computer integration, or hardware-in-the-loop debugging.
• Experience with container orchestration (e.g., k3s, k3d, 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 with common message and open-systems standards such as UCI, OMS, MOSA, or WOSA.
Company:
Shield AI is a deep-tech company that focuses on developing AI-powered systems to enhance the safety of service members and civilians. Founded in 2015, the company is headquartered in San Diego, USA, with a team of 1001-5000 employees. The company is currently Late Stage.