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Staff Software Engineer, Autonomy Capabilities - Space

Shield AI

Job Description

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  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.  

About the Job:

Focusing on the space portfolio, you’ll be creating autonomy capabilities for satellites and missile defense applications that span large-scale distributed optimization, automated tasking and scheduling, track fusion, RPO operations, and space vehicle motion/behavior planning.  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.  In many cases, the capabilities you will develop are at the cutting-edge and so demonstrating the ability to operate in grey space and at the intersection of the state-of-the-now and the state-of-the-possible is both exciting and crucial. 

As a Staff engineer, you will lead the technical delivery of complex autonomy capabilities and demonstrate the ability to operate in significantly more grey space than more junior engineers, helping customers shape their requirements, define technical approaches for the team, and drive technical execution throughout the development process.  You will combine your deep technical expertise with systems-level thinking to deliver scalable and operationally ready autonomy solutions.  

What You'll Do:

  • Multi-Objective Optimization – Use advanced optimization strategies to perform large-scale distributed decision making, task allocation, and resource scheduling in multi-satellite coordinated missions 

  • Weapons Target Assignment – Employ cutting edge approaches for weapons target assignment and motion planning for fleets of space vehicles and interceptors that have critical roles in our national defense 

  • Advance the State of the Art – Pioneer advanced topics in low-SWaP optimal control, tactical behavior management in cooperative and adversarial contexts, and information-aware planning 

  • 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 flight test to ensure seamless integration of autonomy solutions on real-world platforms 

  • Deployment & Test Support – Deploy autonomy capabilities to real space vehicles, supporting 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 10-15% of the year (to different office locations, customer sites, and flight integration events). 

Required Qualifications:

  • Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 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 one or several robotic technology areas related to control systems, motion planning, optimization, tactical behaviors, and/or distributed decision-making 

  • 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, or similar) 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 or higher  

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 

#LD

#LI-ED1

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.

Vacancy posted 2 days ago
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