Senior Staff Engineer, Autonomy Capabilities - Maritime (R5363)

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 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.

\n About the Job:

Focusing on the maritime portfolio, you’ll be creating autonomy capabilities for USVs, UUVs, and cooperating UAVs that enable them to perform advanced single- and multi-agent teaming missions beyond conventional motion planning and waypoint following. The functionality you add will enable teams to use their diverse payloads and maneuvering characteristics to search for, localize, and pursue targets while avoiding sensed threats and obstacles that pose a risk to platform safety. In many of these applications, you’ll have the opportunity to build capabilities from the ground up and be the first to integrate them onto new platforms. You’ll traditionally start with shorter-term R&D efforts or aligned customer programs but with the intent that successful efforts will grow into larger, multi-year programs.

As a Senior Staff Engineer, you will lead the technical direction for the portfolio, driving the evolution of autonomy capabilities and architectures across multiple programs. At this level, you’ll combine your deep technical expertise and systems level thinking to not only provide capabilities that meet the needs of the now, but to anticipate the needs of the future to ensure long-term portfolio success. You’ll take an active role in mentoring engineers across the organization and be a key expert that leadership leans-on for decomposing ambiguous customer needs into tangible design approaches.

What you'll do:

• Robust Motion Planning – Automate unmanned surface vehicle (USV) and/or unmanned underwater vehicle (UUV) maneuvering through advanced motion planning and adherence to safety constraints including keep-out volumes, cooperative and uncooperative vehicles, and depth limitations

• Localization and Tracking – Employ cutting edge approaches for passive and active localization by defining fusion modalities, sensor requirements, and observability-aware maneuvering capabilities to maximize information gleaned from single- or multi-agent sensor networks

• Safe Maritime Operations – Keep vehicle safety as a central focus within autonomous behavior architectures to provide run-time assurance, ensure COLREGS adherence, and build operator trust in advanced mission autonomy

• Heterogeneous Multi-Agent Collaboration – Develop distributed optimization and task allocation approaches for heterogenous teaming in order to accomplish mission objectives by maximally utilizing the diverse capabilities of agents to overall team advantage

• Rigorous Software Development – Develop high-performance software modules that are well-tested, have clear interfaces and span-of-control, and are ready for mid-to-high Technology Readiness Level (TRL) insertions

• Cross-Functional Collaboration – Collaborate with cross-functional teams including perception, planning, simulation, hardware, and operational test to ensure seamless integration of autonomy solutions on real-world platforms

• Deployment & Test Support – Deploy autonomy capabilities to real surface vehicles, supporting integration and demonstration events as well as analysis of mission logs to verify software performance and validate system operational effect

• R&D and Road-mapping – Contribute to autonomy roadmaps by researching and prototyping new algorithms, identifying tactical capability gaps, and proposing novel solutions that advance Shield AI’s mission

• Travel Requirement – Members of this team typically travel around 25% 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 (ideally in the space domain specifically)
• 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 in multiple aerospace domains (e.g., air, land, sea, space)

• Experience across a breadth of methodologies from classical control through optimization and applied ML/RL

• Background in collaborative behaviors and swarm robotics

• Familiarity with domain-relevant DoD or government programs

• Hands-on experience supporting integration events, customer demos, and/or live exercises

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$220,800 - $331,200 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.

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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.