Staff Engineer, Autonomy Software Integration - San Mateo (R4483)

Shield AI•San Mateo, CA

17h

About The Position

Shield AI is seeking an experienced Software Integration Engineer for its Hivemind Quality team. The team integrates, validates, and continuously improves the Hivemind autonomy ecosystem, spanning autonomy behaviors, sensor processing, multi-agent coordination, ground-control systems, and embedded platforms. The role helps autonomy developers build, test, and deploy applications that meet real-world mission objectives. The engineer will become a power user of the Hivemind SDK, develop and validate customer use cases, assess developer usability, and provide feedback to Engineering and Product. The position integrates new autonomy capabilities, evaluates feature completeness, and anticipates customer workflows and edge cases. It bridges engineering development and real-world autonomy applications to help customers build reliable, mission-ready autonomous systems. The work includes integration and validation across simulation, hardware-in-the-loop, and flight environments; bringing autonomy software onto robotic hardware; creating integration and deployment tooling; diagnosing system-level issues; and improving CI/CD workflows and release-readiness processes. Compensation is $188,600–$282,900 per year. Full-time regular employees receive pay within the listed range, bonus, benefits, and equity. Offers are contingent on a cleared background check and possible reference check.

Requirements

Typically at least 7 years of related experience with a bachelor’s degree in computer science, computer engineering, robotics, or a related field; or 6 years with a master’s degree; or 4 years with a PhD.
Proficiency in Python or C++.
Experience with autonomous systems, server applications, or middleware.
Demonstrated experience designing integration workflows, communicating system dependencies, and triaging and reporting defects across subsystem boundaries.
Proficiency with simulation tools and hardware-in-the-loop (HIL) testing environments.
Strong expertise with CI/CD pipelines.
Strong problem-solving skills and a record of delivering high-quality software solutions.
Excellent communication skills and the ability to collaborate across teams and present to customers or technical leadership.

Nice To Haves

Experience building complex systems and a strong understanding of software architecture and design principles.
Experience with hardware or embedded systems.
Expert knowledge of Python.
Experience with ROS.
Experience with white-box testing.
Familiarity with networking, operating systems, and radio communications.
Experience designing automated testing tools for GUI applications.
Experience designing automated testing tools for server applications.

Responsibilities

Develop deep expertise in the autonomy stack and integrate multi-agent systems across simulation, hardware-in-the-loop, and flight platforms.
Integrate autonomy algorithms, perception pipelines, middleware, and platform interfaces, ensuring interoperability between components.
Lead autonomy software integration and platform bring-up on new robotic hardware; configure sensor drivers, communication interfaces, and platform adapters.
Design and implement integration frameworks, deployment scripts, and configuration management tools for SIL, HIL, and flight environments.
Work with integration engineers to support compatibility across platforms, operating systems, and deployment configurations, and resolve integration issues across system boundaries.
Analyze logs, telemetry, and rosbag data to diagnose defects, isolate issues to subsystems, and drive resolution; create tools to accelerate debugging.
Work with DevOps teams to improve integration pipelines, shorten build-to-deploy cycles, and support continuous integration of new features.
Define integration checkpoints and release-readiness criteria.
Help verify that integrated capabilities meet product requirements and interface specifications, including tooling for end-to-end compliance and traceability.
Develop customer use cases, evaluate SDK usability, and provide actionable feedback to Engineering and Product teams.
Assess feature completeness and anticipate customer workflows and edge cases.