Senior Staff Software Engineer, Autonomy Capabilities (R4587)

Shield AI
San Mateo, CA
On-site

In the 12 months to 30 Jun 2026, Shield AI filed 1 H-1B position titled "Senior Engineer, Integration and Software". Source: U.S. Department of Labor, LCA disclosure data. A record of filings already made, not a commitment to sponsor.

Who this role is best for

Aimed at senior-level engineers with a strong background in robotics and autonomy systems who enjoy cross-functional collaboration and real-world deployment.

Best fit for

  • Candidates with 10+ years of experience in robotics and autonomy algorithm development for defense systems
    — “Typically requires a minimum of 10 years of related experience with a Bachelor’s degree”
  • Individuals who can bridge classical control systems with machine learning techniques in dynamic environments
    — “Work at the intersection of classical autonomy and machine learning”
  • Engineers who have participated in field testing and have a proven track record in deploying real-world systems
    — “Deploy autonomy capabilities to real platforms and participate in field tests”

Things to consider

  • Travel is a regular requirement, with 10-15% of the year spent traveling for testing and integration
    — “Members of this team typically travel around 10-15% of the year”
  • The role demands a balance between theoretical research and practical implementation for immediate program impact
    — “balancing theory with practice and rigorous implementation is paramount”

How to stand out

  • Highlight experience with multi-agent coordination and behavior modeling in dynamic environments
    — “Implement and test behavior architectures that enable multi-agent coordination”
  • Showcase your ability to integrate autonomy solutions into real-world platforms with operational relevance
    — “Developed solutions are expected to be integrated into real-world platforms”
  • Emphasize your background in simulation tools like AFSIM and NGTS for testing and validation
    — “Experience with simulation tools and environments (e.g., AFSIM, NGTS)”
  • Demonstrate your ability to analyze mission data and optimize behavior models iteratively
    — “Analyze mission logs and performance data to diagnose failures, optimize behavior models”
  • Position yourself as someone who can adapt autonomy solutions to evolving defense program requirements
    — “Support defense-focused programs and customer needs by adapting autonomy solutions”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • developing tactical autonomy algorithms
  • implementing behavior architectures
Typical background
software engineeringautonomy systems

Skills & requirements

Required

Autonomy SoftwareMulti-agent CoordinationHigh-performance Software Development

Preferred

Reinforcement LearningSimulation

Stack & domain

Autonomy AlgorithmsHigh-performance Software DevelopmentBehavior ArchitecturesMulti-agent CoordinationReinforcement LearningCross-functional CollaborationField TestingMission Data AnalysisR&DProblem-solvingTeamworkCommunicationAdaptabilityLeadershipDefense TechAutonomy SoftwareAircraftSimulationSynthetic Reality

About the role

Original posting from Shield AI via Lever

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 Autonomy Capabilities Team develops functionality to automate single- and multi-agent teams of platforms in pursuit of mission objectives and acts as a central discipline-aligned focal-point for encouraging consistent usage of technical approaches across business portfolios.  This team operates at all levels of the command-and-control hierarchy (from advanced control laws, through motion planning, and up to advanced tactical behaviors and multi-agent coordination) and across a multitude of mission sets, platform types, and operational domains (e.g., air, sea, space).  The team puts a strong emphasis on both fundamentals (e.g., aircraft kinematics/dynamics, trajectory design, optimization, information fusion, efficient algorithms, etc.) and software integration skillsets (e.g. structures, protocols, threading, interface management, etc.) to bring market-differentiating capabilities to customers that seamlessly operate within their integration contexts. 

This position is perfect for an individual who enjoys solving complex problems across a diverse set of programs and integration contexts. An ideal candidate is expected to address operational system needs through a multitude of advanced methodologies that blend traditional control system approaches with advanced optimization. Developed solutions are expected to be integrated into real-world platforms with near-term program impacts and rewards and so balancing theory with practice and rigorous implementation is paramount.  

What you'll do::

  • Tactical Autonomy Design – Design tactical autonomy algorithms to enable unmanned aircraft to perform complex missions across air, land, and sea domains with minimal human supervision.
  • High-Performance Software Development – Develop high-performance software modules that incorporate planning, decision-making, and behavior execution strategies for dynamic and adversarial environments.
  • Behavior Architecture Implementation – Implement and test behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios.
  • Hybrid Autonomy Integration – Work at the intersection of classical autonomy and machine learning, blending rule-based systems with learning-based methods such as reinforcement learning to achieve robust, adaptive behavior.
  • Cross-Functional Collaboration – Collaborate with cross-functional teams including perception, planning, simulation, hardware, and flight test to ensure seamless integration of autonomy solutions on real-world platforms.
  • Deployment & Field Testing – Deploy autonomy capabilities to real platforms and participate in field tests and flight demos, validating performance in operationally relevant conditions.
  • Mission Data Analysis – Analyze mission logs and performance data to diagnose failures, optimize behavior models, and inform iterative development.
  • R&D and Roadmapping – Contribute to the autonomy roadmap by researching and prototyping new algorithms, identifying tactical capability gaps, and proposing novel solutions that advance Shield AI’s mission.
  • Program Support & Adaptation – Support defense-focused programs and customer needs by adapting autonomy solutions to evolving mission sets, compliance requirements, and operational feedback.
  • Travel Requirement – Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight 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 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 programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS).
  • Significant background in robotics technologies related to motion planning, behavior modeling, decision-making, or autonomous system design. 
  • Significant experience with unmanned system technologies and accompanying algorithms (specifically air domain) 
  • Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation.
  • Strong problem-solving skills, with the ability to troubleshoot and optimize system performance.
  • 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 applying ML/RL techniques in autonomy pipelines.
  • Background in collaborative behaviors, swarm robotics, or distributed decision-making.
  • Familiarity with tactical behaviors for unmanned systems in DoD or government programs.
  • Work on behaviors applicable across air, ground, and maritime vehicles.
  • Hands-on experience supporting flight demos or live exercises.
  • Experience with UCI and OMS Standards

#LI-ED1

#LE

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.

Source: Shield AI careers (Lever)

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