AI Engineer

Leidos has a new and exciting opportunity for a AI Engineer in our National Security Sectors (NSS) Cyber & Analytics Business Area (CABA). Our talented team is at the forefront in Security Engineering Computer Network Operations (CNO) Mission Software Analytical Methods and Modeling Signals Intelligence (SIGINT) and Cryptographic Key Management. At Leidos we offer competitive benefits including Paid Time Off 11 paid Holidays 401K with a 6% company match and immediate vesting Flexible Schedules Discounted Stock Purchase Plans Technical Upskilling Education and Training Support Parental Paid Leave and much more. Join us and make a difference in National Security!

The program is seeking an AI Engineer with a proven track record in software engineering and deep understanding of Artificial Intelligence/Machine Learning (AI/ML) techniques to support the exciting new AI-Assisted development mission. The AI engineer will work closely with mission stakeholders to capture requirements aid in structured planning and improve the certification process by introducing AI/ML tooling. Additionally the engineer will use AI/ML to develop tools and techniques to include fine tuning Large Language Models (LLM) that assist in enhanced vulnerability identification and mitigation capabilities.

Position Responsibilities:

• Lead AI development across a 20 person engineering team supporting AIenabled software modernization.

• Build AI/ML tools including LLM orchestration RAG pipelines automation workflows and missionfocused applications.

• Collaborate with customers through technical meetings architecture reviews and briefings.

• Design AI system architectures integration strategies secure APIs and userfacing tools.

• Integrate AI into engineering workflows for requirements analysis code generation testing vulnerability scanning and release processes.

• Configure AI agents plugins and automation frameworks to boost developer productivity.

• Develop documentation including user guides API references and operational playbooks.

• Support deployment and testing of AIenabled systems in secure environments.

• Optimize AI models for performance scalability and mission reliability.

• Ensure security compliance in partnership with cybersecurity and DevSecOps teams.

REQUIRED QUALIFICATIONS:

• Bachelors Degree in System Engineering Computer Science Information Systems Engineering Science Engineering Management or a related field and at least 8 years of related experience. Additional experience may be substituted for a Degree.

• AI-Enabled SDLC Architecture: Experience designing or implementing AI-enabled software development lifecycle (SDLC) architectures and developer productivity platforms. Familiarity with internal developer portals CI/CD automation software delivery tooling and secure development workflows. Understanding of how AI coding agents integrate across the full SDLC including requirements analysis system design implementation code review automated testing security scanning release management documentation generation and operational support.

• AI Coding Agent Experience: Hands-on experience using configuring or extending AI-assisted development tools and coding agents such as OpenCode Claude Code GitHub Copilot Cursor Aider Continue Sourcegraph Cody or similar agentic development environments. Understanding of how coding agents perform repository inspection task planning code modification command execution diagnostic interpretation and iterative remediation workflows.

• OpenCode Extensibility & Workflow Integration: Experience configuring or extending OpenCode or similar agentic development platforms through custom agents tools plugins hooks and workflow integrations. Familiarity with integrating external services and automation pipelines using MCP servers plugin frameworks and event-driven customization mechanisms.

• Model Context Protocol (MCP) Expertise: Experience building integrating or securing Model Context Protocol (MCP) servers and clients. Understanding of MCP concepts including tools resources prompts transports authentication authorization permissions management context isolation and safe execution boundaries. Familiarity with enabling AI systems to securely interact with local filesystems APIs databases search services and mission-specific workflows.

• Secure AI Engineering: Understanding of secure AI development practices AI governance model safety prompt injection mitigation data protection and secure integration of LLM-powered systems within classified or restricted computing environments.

• Modern AI Infrastructure: Experience deploying and operating AI/ML services in containerized and orchestrated environments using Kubernetes Docker or cloud-native MLOps platforms. Familiarity with scalable inference architectures GPU-enabled workloads and automated model deployment pipelines.

• Must possess an active Secret clearance to be considered and would be eligible to obtain up to a TS/SCI clearance in the future.

• DoD 8570 approved security certification (i.e. Security ) (Will be required 90 days after hire).

DESIRED QUALIFICATIONS:

• Experience working in all phases of the engineering product development lifecycle.

• Experience with Agile Scrum methodology.

• Active Top Secret/SCI Clearance

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

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline onlyand 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.