Senior AI Software Engineer

Leidos is seeking an Senior AI Software Development Engineer to join the Air Traffic Business Area within the Homeland Sector , based in Eagan, MN to support the development of the Leidos Common Automation Platform (L-CAP). L-CAP is a mission-critical, future-ready automation solution built on a hybrid cloud data mesh architecture. As a member of a large-scale, Scaled Agile software development organization, you will contribute to the technical execution of a program that integrates proven, globally deployed technologies with modern cloud-native and AI-enabled capabilities. You will work alongside cross-functional teams and technical leaders to deliver predictable outcomes in a highly regulated, safety-critical environment. In this position, you will design and implement software solutions independently while working closely with systems engineering, product delivery, and DevSecOps teams. The primary focus is on developing microservices-based applications within an Agile/SAFe environment. Experience with AI-enabled or data-driven systems is advantageous. This position supports government programs and requires the ability to obtain and maintain a Public Trust clearance . Hybrid Schedule is 3 days onsite and 2 days remote. Key Responsibilities Design, develop, and maintain microservices-based applications using modern software engineering best practices Collaborate with product owners, architects, and engineers in an Agile / SAFe environment Participate in sprint planning, daily standups, reviews, and retrospectives Collaborate with systems engineering, product delivery, and program teams to translate requirements into working software solutions. Develop clean, maintainable, and testable code following CI/CD and DevSecOps practices Contribute to system design discussions and technical decision-making Integrate services with databases, messaging systems, and external APIs Support troubleshooting, performance tuning, and continuous improvement Work closely with QA, DevOps, and platform teams to ensure reliable delivery Required Qualifications Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience) 12+ years of relevant experience or 10+ years of experience with a Master's Degree Hands-on experience building and supporting microservices-based systems Proficiency in at least one modern programming language (e.g., Java, Python, C++, or similar on a Linux based system) Experience working in Agile environments Understanding of APIs and distributed system concepts Ability to obtain and maintain a Public Trust clearance U.S. citizenship required Preferred / Desired Qualifications Experience or exposure to AI/ML-enabled systems (Claude-Code) , automation, or intelligent platforms. Experience with Git-based version control and CI/CD pipelines Familiarity with Scaled Agile Framework (SAFe) Experience working with relational and/or NoSQL databases Hands-on experience with Kafka or other event-streaming technologies Cloud experience (AWS, Azure, or GCP) Containerization and orchestration experience (Docker, Kubernetes) Experience working in DevSecOps environments Additional Requirements Successful completion of background investigation as required by the government customer 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:

February 18, 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.