Staff Engineer, Software - Autonomous Aircraft Integration (R4983)
Shield AI is hiring a Staff Engineer, Software - Autonomous Aircraft Integration (R4983) in Washington DC, United States. It pays $183k-$274k a year and Level rates it ; you can apply on Shield AI.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- Level classifies it as a lead role.
- Level lists 659 other open roles at Shield AI.
AI in this role
This position is ideal for an individual who thrives on solving complex integration challenges that span hardware, software, and systems engineering. A successful candidate will be skilled at deploying autonomy solutions onto unmanned platforms, preparing systems for flight, and troubleshooting mission-critical issues in both lab and field environments. The role is highly dynamic, requiring hands-on experience, strong systems thinking, and the ability to operate effectively in fast-paced, real-world test conditions. Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Flight Integration Engineers are essential to bridging the gap between R&D and deployment, ensuring that autonomous systems function reliably and effectively when and where they are needed most.
What you'll do:
- System Integration & Deployment — Integrate autonomy software onto unmanned aircraft systems, ensuring seamless operation across onboard compute, sensors, and control interfaces.
- Pre-flight Preparation — Own the build, configuration, and validation process for flight-ready systems; coordinate hardware/software compatibility and mission readiness.
- On-site Flight Test Support — Travel to test sites and support live flight operations, including safety checks, system bring-up, and troubleshooting under time-critical constraints.
- Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy software stacks and embedded systems in lab and field environments.
- Flight Data Capture & Analysis — Manage data collection during missions and post-test analysis, working with autonomy engineers to refine behaviors and identify improvements.
- Collaboration Across Teams — Work closely with autonomy, GNC, systems, and test teams to ensure mission-critical functionality is delivered on time and validated thoroughly.
- Continuous Improvement — Build tools and processes to improve integration timelines, flight test reliability, and team efficiency across deployment cycles.
- Support Certification and Compliance — Assist with documentation and system-level validation required for certification, airworthiness, and compliance in defense-relevant environments.
- Travel Requirement – Members of this team typically travel around 30-40% 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 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.
- Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS).
- Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics.
- Knowledge of sensor integration, sensor fusion, and middleware frameworks (e.g., ROS, DDS).
- Hands-on experience supporting flight demos or live exercises.
- 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:
- Direct experience supporting unmanned aerial systems or similar flight test campaigns.
- Familiarity with autonomy stacks, flight control systems, or GNC pipelines.
- Competence in sensor integration, electronics debugging, or avionics bring-up.
- Proficiency in developing automation tools for system testing, logging, and data parsing.
- Comfortable interfacing with DoD stakeholders during field events or technical reviews.
- Experience with UCI and OMS Standards.
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.
How we rate this
Staff Engineer, Software - Autonomous Aircraft Integration (R4983) at Shield AI rates 27 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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