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Staff Systems Engineer - Payload Lead

Anduril · Costa Mesa, California, United States

Location
Costa Mesa, California, United States
Salary
$191,000 - $253,000 USD
Funding
$3.7B
Posted
Sep 18, 2026

Anduril is hiring a Staff Systems Engineer - Payload Lead based in Costa Mesa, California, United States. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.

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Role details

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. ABOUT THE TEAM The Maneuver Dominance team is building Thunder - an autonomous attack rotorcraft built to fight alongside crewed combat aviation to deliver overwhelming mass effects deep beyond the front lines. The team builds the Mission System and the autonomy that makes aircraft like Thunder work. Autonomy is only as good as the link that carries it. Thunder is a compact airframe with weapons, sensors and radios competing for the same antenna real estate, flying low and in formation, in a spectrum that is actively contested. That is the problem you would own. ABOUT THE JOB Anduril is seeking a Staff Systems Engineer to support payloads integration for the Thunder team. The Maneuver Dominance (MD) Team at Anduril develops aerial robotic systems designed to operate in large coordinated teams in concert with ground maneuver forces. WHAT YOU’LL DO Drive the perception system architecture and requirements baseline: decompose mission need into detection, range, field of regard, latency, and availability requirements, allocate them across sensing, compute, and algorithms, and keep them traceable through to test evidence Own the sensor suite baseline and its configuration across platforms, including which modalities and part numbers are in the baseline for each aircraft variant, where they are installed, and the interfaces to the programs and airframes that carry them Set and defend the sensing performance model: detection probability and false alarm rate against target size, reflectivity, range, aspect, illumination, and weather, built up from radiometry and detector performance, and reconciled against measured flight test results Drive the verification and validation strategy for perception: verification plans, bench and hardware in the loop coverage, sensor characterization test, flight test objectives, data collection needs, and the evidence package that demonstrates a capability is ready to graduate onto a program aircraft Provide the technical authority at design and gate reviews, judging whether perception evidence is sufficient and coverage is complete, and holding the line when it is not Lead sensor trades that resolve real forks, framing the decision, defining the criteria, running the analysis, and documenting the result so it survives the people who made it Drive modularity and reuse so that perception ports across platforms, including sensor abstraction, interface stability under sensor substitution, and open mission system alignment Set the sensing engineering practice that others inherit: how we model performance, how we characterize a sensor, and what constitutes proof, so that each new effort starts from an established method rather than reinventing one Own perception in the air: instrument flight tests, be at the aircraft for them, and drive the analysis loop from collected data back into requirements and architecture Represent Anduril externally as a technical authority on airborne sensing, including standards and industry bodies, sensor vendors and development partners, and technical engagement with customers REQUIRED QUALIFICATIONS: B.S. or M.S. in Electrical Engineering, Optics, Physics, Computer Science, Robotics, Aerospace, or a similar field, or equivalent experience 5+ years of engineering experience on electro-optical, LiDAR, RADAR, or comparable sensing systems, including time as the technical owner of a sensing system through to fielded or flight demonstrated performance Demonstrated depth in multi-modal sensor architecture and sensor selection, with a working command of the detection physics that bounds each one Demonstrated experience owning system architecture and interface definition for a sensing system, including the interfaces to compute, to autonomy consumers, and to the vehicle Ability to exercise extremely high ownership over a complex system across design, integration, test, and flight test Demonstrated experience specifying and verifying sensing performance quantitatively, including detection and false alarm characterization, range performance analysis, and validation of a model against measured data Working command of electro-optical, LiDAR, and/or RADAR system engineering fundamentals: radiometry and link budgets, detector and optics selection, noise and sensitivity metrics such as NETD and NEP, resolution and MTF, and atmospheric transmission and its effect on range Demonstrated experience with the systems engineering rigor this role sits on: requirements management, traceability to verification, ICDs, and technical performance measures as a managed baseline Outstanding written and verbal communication, including presenting and defending technical positions to program leadership, to engineering peers who disagree, and to audiences outside the company such as standards bodies, development partners, and customers Must be eligible to obtain and maintain a US Top Secret security clearance PREFERRED QUALIFICATIONS: Experience with learned perception in a safety relevant system, including evaluation gates, dataset and labeling strategy, and the argument for why a model's measured performance is trustworthy Experience with embedded compute and SWaP-C budgeting for airborne perception, including latency budgets end to end from photon to autonomy i

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