Leidos Intelligence Sector delivers advanced technology and mission software across cyber, logistics, security operations, and decision analytics, empowering defense and intelligence customers to stay ahead of evolving global threats.
Our mission is simple: equip those who protect the nation with the tools, technologies, and insights they need to succeed in an increasingly complex security landscape.
We are seeking a Senior Software Engineer who doesn’t just build systems, but redefines how they are imagined, developed, and deployed. In this role, you will act as both a lead engineer and technical innovator, driving the design and delivery of AI-enabled, agentic, and intelligent software platforms that accelerate modernization and mission outcomes. You will operate across the full spectrum, from shaping technical strategy and evaluating emerging technologies to prototyping and delivering production-grade solutions.
We’re looking for builders who move with urgency, think boldly, and execute with discipline. You’ll work in a highly collaborative environment, developing scalable, high-quality software while influencing the direction of next-generation capabilities.
The ideal candidate brings strong object-oriented design fundamentals, deep backend engineering experience, and a passion for solving complex problems at scale. You will contribute across the full software lifecycle while continuously improving performance, reliability, and user experience.
Primary Responsibilities
• Design, build, and scale distributed, cloud-native and on-premise systems, including developer platforms and mission-critical applications.
• Develop and deploy AI-enabled applications, including integration of large language models (LLMs), retrieval-augmented generation (RAG), and agentic workflows into production environments.
• Architect and implement solutions using modern AI/ML frameworks, orchestration tools, vector databases, and microservices-based architectures.
• Write high-quality, maintainable code in multiple programming languages (e.g., Python, Java, C++, Go), leveraging AI-assisted development tools to accelerate delivery and improve productivity.
• Leverage AI to analyze, modernize, and refactor large, complex codebases (e.g., Java, .NET, COBOL, C++).
• Design and optimize end-to-end AI workflows, including prompt engineering, model evaluation, fine-tuning, and continuous improvement of model performance.
• Develop and maintain CI/CD pipelines and automated testing frameworks to support rapid, reliable software delivery across environments (on-prem, AWS, Azure).
• Apply DevSecOps principles to ensure secure, resilient, and compliant software solutions, particularly in government or mission-focused environments.
• Lead and contribute to technical architecture decisions, ensuring alignment with best practices in scalability, performance, and maintainability.
Basic Qualifications
• Bachelor's degree and 12+ years experience in software engineering, including significant experience at the senior/architect level. Additional experience may be considered in lieu of a degree.
• Expertise in designing and building distributed systems, developer tools, or platform engineering products.
• Hands-on experience implementing AI/ML systems or integrating large language models into production workflows.
• Strong knowledge of agentic frameworks, orchestration tools, RAG, vector databases, API design, and microservices.
• Deep understanding of software design patterns, CI/CD, DevSecOps, and cloud-native architectures (AWS/Azure/GCP).
• Strong coding proficiency in at least two modern languages (Python, Go, Java, C#, etc.).
• Experience supporting full software development lifecycle (SDLC) from design through deployment and sustainment.
• Proven ability to work independently and lead within Agile/Scrum teams. Experience mentoring junior engineers and guiding best practices. Strong communication skills to translate complex technical concepts to stakeholders.
• Must be authorized to work in the U.S.
• Must live in the National Capital Region area and be able to commute to the Leidos GHQ office. Flexible to work remote with the ability to commute to the corporate office as needed
• Must have active TS clearance with ability to obtain and maintain a TS/SCI security clearance
Preferred Qualifications
• Experience leading or contributing to enterprise-wide code reuse, standardization, and modernization initiatives
• Familiarity with developer experience (DevEx) improvements, including tooling, workflows, and platform engineering concepts
• Hands-on experience with static analysis, code quality, and security scanning tools (e.g., SonarQube, Fortify, Checkmarx)
• Experience working in cloud environments (AWS, Azure, GCP), including hands-on experience with AWS services such as EC2 and S3, and deploying applications in containerized architectures (Docker, Kubernetes)
• Working knowledge of multiple programming languages and the ability to operate across diverse technology stacks
• Experience establishing and managing software baselines, inventories, and asset catalogs
• Familiarity with open-source frameworks and approaches for evaluating and adopting emerging technologies
• Experience developing and visualizing engineering metrics and performance dashboards
• Background supporting federal, intelligence, or homeland security missions
• TS /SCI with poly clearance
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.
April 21, 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 $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.