Software Engineer- AI, Autonomy and Platform Development

Leidos•San Diego, CA

3d•$107,900 - $195,050

About The Position

Leidos Office of Technology is seeking software engineers with AI and autonomy experience to build a common technology platform. Engineers design, build, and operate production software for AI-driven and autonomous systems in small, accountable build-and-run teams. The work supports national security and other critical missions where reliability, security, and human oversight are important. The role uses AI-assisted development practices to help deliver software faster and at higher quality. The ideal candidate will be based in Northern Virginia or near another Leidos facility, such as Huntsville, Alabama, or San Diego, California. Onsite work at a Leidos facility is required as business needs dictate. The position is open to engineers from junior through senior levels, with opportunities tailored to individual experience and expertise.

Requirements

At the early-career level, a bachelor's degree in Computer Science, Software Engineering, or a related technical field and 4 or more years of experience; additional years of experience may be considered in lieu of a degree.
At the mid level, a bachelor's degree in Computer Science, Software Engineering, or a related technical field and 8 or more years of experience; additional years of experience may be considered in lieu of a degree.
At the senior level, a bachelor's degree in Computer Science, Software Engineering, or a related technical field and 12 or more years of experience; additional years of experience may be considered in lieu of a degree.
Hands-on software development experience in one or more modern languages such as Python, C++, Rust, Java, Go, or TypeScript.
Experience building AI/ML-enabled or autonomous systems, through professional work, academic work, or personal projects; examples include LLM agents, robotics, perception, planning, or sensor-driven software.
Working knowledge of Git-based workflows, CI/CD, automated testing, and DevSecOps practices.
Experience using AI-assisted development tools such as GitHub Copilot, Cursor, or Claude Code, or comparable tools, and ability to adopt new tools quickly.
Strong communication skills and ability to work effectively in small, cross-functional teams.
U.S. citizenship and the ability to obtain and maintain a Top Secret security clearance.

Nice To Haves

Experience building AI/ML-enabled systems, including LLM agents, agent frameworks, evaluation harnesses, or retrieval and data pipelines.
Experience with autonomy or robotics software, including perception, planning, control, sensor fusion, simulation, ROS 2, or DDS.
Experience with edge and embedded systems, real-time or deterministic software, Linux and real-time operating systems, or GPU/accelerator programming.
Experience designing APIs, SDKs, or developer platforms, including extensible component architectures, developer experience, platform engineering, or software modernization.
Experience with cloud and container technologies such as AWS, Azure, or Google Cloud, and Docker, Kubernetes, or infrastructure as code.
Familiarity with secure software supply chain practices, static analysis, and security scanning tools such as SonarQube, Fortify, or Checkmarx.
Understanding of responsible AI practices for assured autonomy, including human-in-the-loop control, audit trails, and IP and data-handling considerations in AI-assisted development.
Background supporting federal, defense, intelligence, or homeland security missions, and an active Top Secret clearance.

Responsibilities

Design and build AI agents and reasoning services, including LLM-based agents, planning, and inference, with human oversight, auditability, and fail-safe behavior.
Develop autonomy software and integrate it with sensors, platforms, and hardware across edge and cloud environments.
Design and develop platform software, including APIs and SDKs, data and knowledge services, and user-facing applications.
Package components as reusable, secure, well-documented assets that others can adopt without rework.
Build and maintain CI/CD pipelines, automated testing, and release evidence such as SBOM, provenance, and signing.
Own software in production, including observability, reliability, and incident response.
Contribute to engineering standards, reusable patterns, and technical-debt reduction across the platform.
Collaborate with program teams and architects to translate customer needs into repeatable capabilities.
Use AI-assisted development tools in daily engineering and help teams adopt them effectively and responsibly.
Evaluate emerging AI, autonomy, and developer-productivity technologies and scale effective approaches.