Lead DevSecOps Software Developer

Leidos•Gaithersburg, MD

1d•Hybrid

About The Position

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 Gaithersburg, MD . 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.

Requirements

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

Nice To Haves

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 of federal security frameworks such as NIST RMF, NIST 800-53, or CIS benchmarks
Experience developing and integrating RESTful APIs and distributed systems
Experience with observability and monitoring tools (e.g., Prometheus, Grafana, ELK stack)
Experience with serverless and event-driven architectures
Relevant certifications (e.g., AWS Certified DevOps Engineer, Certified Kubernetes Administrator, Security+)

Responsibilities

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