Job Description
Description Leidos is seeking a Lead DevSecOPS Soft ware Developer to join the Air Traffic Business Area within the Homeland Sector , supporting the development of the Leidos Common Baseline . Common Baseline is a mission-critical, future-ready automation solution built on a hybrid cloud data mesh architecture. As a member of a 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 focus on building and integrating shared services, pipelines, and tooling that standardize DevSecOps practices enterprise-wide. The selected candidate will combine strong integration skills with an emerging focus on AI-enabled automation to drive efficiency, consistency, and security across mission systems. This position supports government programs and requires the ability to obtain and maintain a favorable Public Trust investigation This position is located in either Gaithersburg, MD or Egg Harbor Township, NJ . This is an opportunity to contribute to projects that impact millions of air travelers. This is a hybrid position requiring 3 days onsite and 2 days working from home. This role focuses on building and modernizing real-time, safety-critical systems using a combination of traditional systems engineering and AI-augmented software development practices. You’ll work on software that directly supports national air traffic operations, applying AI tools to accelerate development, improve quality, and enhance system reliability. What You’ll Do Design, build, and maintain a Common Automation Platform supporting CI/CD, security, and infrastructure automation Develop reusable automation frameworks, templates, and pipelines for enterprise-wide adoption Integrate platform capabilities with internal and external systems via APIs, microservices, and event-driven architectures Embed security controls and DevSecOps best practices into platform services and workflows Implement infrastructure-as-code (IaC) to provision and manage scalable environments Enable self-service capabilities for development teams through automation and platform tooling Implement automated security testing including SAST, DAST, container, and dependency scanning Support containerized workloads using Docker and Kubernetes Apply AI/ML capabilities to enhance automation (e.g., intelligent pipeline optimization, anomaly detection, auto-remediation) Collaborate with engineering, security, and operations teams to drive platform adoption and standardization Monitor platform performance, reliability, and usage metrics, and continuously improve capabilities Ensure compliance with federal security standards and organizational policies Core Technical Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience) 4+ years of relevant experience or a Master's Degree and 2+ years Experience building or supporting shared platforms, developer platforms, or automation frameworks Experience with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions Experience with cloud platforms such as AWS Proficiency in scripting or programming languages such as Python or Bash Experience with containerization (Docker) and orchestration (Kubernetes) Experience with security tools and practices including vulnerability scanning, secrets management, and identity/access management Experience with IaC tools such as Terraform Familiarity with infrastructure-as-code and configuration management tools Strong problem-solving skills and ability to work in a collaborative team environment Ability to obtain and maintain a Public Trust U.S. citizenship required Must be able to successfully complete future background investigations as required by the government customer Preferred / Desired Qualifications Experience designing or implementing internal developer platforms (IDP) or platform engineering concepts Experience applying AI/ML or intelligent automation within DevSecOps pipelines Familiarity with MLOps concepts and frameworks Knowledge o