Lead Software Engineer – AI-Assisted Development

This is a special, high-impact leadership role. Beyond delivering mission software, you will serve as the team’s technical lead and the driving force for AI-assisted software engineering – bringing modern, agentic AI coding practices to the program and coaching the team so that every engineer becomes measurably more productive. The ideal candidate has built real production software with current-generation agentic AI coding assistants and can adapt those practices to a secure environment where the newest commercial tooling is often restricted. You will start as the technical lead for the software team, with a defined growth path into a people-management role as the team scales.

Primary Responsibilities

• Serve as the technical lead and design authority for the IFPC Agentic AI software development improvement software team, setting technical direction, mentoring engineers, and driving quality and delivery, with a defined growth path into a people-management role as the team scales.
• Champion and operationalize agentic AI-assisted software development across the team: establish the workflows, agent/prompt patterns, custom tooling, and guardrails that measurably multiply the team’s throughput and code quality.
• Coach and upskill engineers in the effective, responsible use of AI coding assistants through hands-on pairing, enablement sessions, code reviews, and reusable playbooks, acting as a force multiplier for the entire team.
• Adapt commercial agentic-AI coding practices to a secure, restricted, or air-gapped environment; evaluate, pilot, and shepherd AI tooling through the security-approval process, including on-prem / self-hosted model options.
• Develop production software in C++ and Python in a Linux environment for counter-UAS and missile defense systems.
• Develop within a SAFe environment using Jira and GitLab; apply software best practices such as peer reviews, unit testing, and CI/CD automation – integrating AI responsibly into the software development lifecycle.
• Debug and troubleshoot software in a Hardware-in-the-Loop (HWIL) and Software-in-the-loop (SWIL) setting.
• Establish and enforce engineering and coding standards, and drive standardized, reusable, well-documented solutions.
• Collaborate across systems, electrical, test, and cybersecurity teams, and interface with program leadership and the customer to align software delivery with program needs.

Basic Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related technical discipline and 12+ years of professional software development experience (or Master’s degree + 10 years / PhD + 7 years).
• Recent, substantial, hands-on experience building real software with current-generation agentic AI coding assistants and AI-assisted development workflows, not just experimentation.
• Demonstrated ability to coach and mentor engineers and to lead a software team as a technical lead.
• Strong, current proficiency in C++ and Python.
• Experience across the full software lifecycle, including peer reviews, automated testing, and CI/CD.
• Experience working within an Agile / SAFe environment (or equivalent).
• Experience with tools such as Jira and GitLab (or equivalent).
• Experience developing in a Linux environment.
• Ability to adapt modern AI-assisted development workflows to security-constrained, restricted, or disconnected environments (or a clear, demonstrated capacity to do so).
• Currently living in Huntsville, AL or willing to relocate.
• U.S. Citizen with the ability to obtain and maintain a Secret security clearance (interim and final).

Preferred Qualifications

• Deep, hands-on expertise with specific agentic AI coding tools – e.g., Claude Code, Cursor, GitHub Copilot / Copilot Workspace, Windsurf, Aider – and with Model Context Protocol (MCP)-based agent and tool workflows.
• Experience building AI enablement assets: prompt/agent libraries, custom skills/agents, and automated code-review and test-generation pipelines that scale across a team.
• Experience measuring and driving AI developer-productivity impact (e.g., DORA metrics, cycle time, review latency) and leading tool adoption at team or organization scale.
• Experience with self-hosted / on-prem large language models and retrieval-augmented generation (RAG) over codebases (e.g., vLLM, Ollama, Amazon Bedrock / GovCloud), including deployment in disconnected environments.
• Familiarity with AI governance and safety for software teams: secure use of AI on sensitive code, data-handling, and intellectual-property and security guardrails.
• Commercial / private-sector software experience where access to state-of-the-art agentic AI coding tools is widespread.
• Counter-UAS, missile defense, or other mission-system domain experience.
• Real-time / embedded C++ and experience troubleshooting/testing software in an HWIL environment.
• Experience with Buildroot and VMware; network programming (UDP/TCP) and analysis tools such as Wireshark.
• Experience supporting and maintaining CI/CD pipelines, and familiarity with DoD acquisition processes and methods.

At Leidos, we outthink, outbuild, and outpace the status quo – because the mission demands it. If you’re ready for your next career challenge, we want to hear from you.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

September 23, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $131,300.00 - $237,350.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.