Sobre este puesto de Lead DevSecOps Engineer en Leidos
Leidos is seeking a Lead DevSecOps Engineer to join the Air Traffic Business Area within the Homeland Sector, supporting the development of the Leidos Common Automation Platform (L-CAP). L-CAP is a mission-critical, future-ready automation platform built on a hybrid cloud data mesh architecture, enabling next-generation air traffic management capabilities. We are building with an AI-first engineering mindset, embracing emerging AI capabilities and modern development practices to accelerate delivery, improve software quality, and continuously evolve how we design and build mission-critical systems. This role operates within a SAFe/Agile framework as part of an Agile Release Train (ART) delivering iterative value across the program. 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; Egg Harbor Township, NJ; or Eagan, MN. 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, if you are located within a commutable distance (Less than 1 hour's drive one-way during normal traffic) from Gaithersburg, MD; Eagan, MN; or Egg Harbor Township, NJ. However, if you do not reside within a commutable distance, you may be considered for a 100% remote role.
What you'll do:
Build and maintain CI/CD pipelines enabling continuous integration, testing, and delivery for L-CAP
Manage Kubernetes clusters and container orchestration for platform service deployments
Develop and maintain infrastructure-as-code (IaC) using Terraform for repeatable environments
Integrate security scanning tools (SAST, DAST, SCA) into CI/CD pipelines for shift-left security
Manage container images, registries, and deployment artifacts across environments
Automate operational tasks including provisioning, scaling, and configuration management
Manage development, test, and production environments ensuring consistency and reliability
Implement monitoring, logging, and alerting solutions for platform observability
Collaborate with development teams to improve build times, deployment frequency, and reliability
Support incident response and troubleshooting of infrastructure and deployment issues
Implement software supply chain security controls including SBOM generation, artifact signing, and dependency vulnerability scanning
Manage artifact repositories and build provenance ensuring integrity of software deliverables throughout the pipeline
Support developer platform capabilities including self-service environment provisioning, documentation, and developer experience improvements
Embrace an AI-first engineering culture by actively adopting AI-assisted development tools, automation, and modern engineering practices that improve productivity, code quality, and delivery velocity.
Core Technical Qualifications:
Bachelor’s degree in Computer Science, Information Technology, or related discipline with 4 or more years of experience (or Master’s degree with 2 or more years of experience) or equivalent experience in lieu of degree.
Experience building and maintaining CI/CD pipelines (Jenkins, GitLab CI, or GitHub Actions)
Hands-on experience with Kubernetes cluster management and container orchestration
Proficiency with Terraform or equivalent infrastructure-as-code tools
Strong experience with Docker and containerization technologies
Solid Linux systems administration skills
Proficiency in scripting languages (Bash, Python) for automation
Experience with security scanning tools and DevSecOps practices
Understanding of networking, load balancing, and service mesh concepts
Familiarity with Agile/SAFe delivery and DevOps culture
Experience with software supply chain security tools (Sigstore, SLSA, SBOM generation)
Knowledge of artifact management systems and build provenance tracking
Experience supporting internal developer platforms and developer experience initiatives
Ability to obtain and maintain a Public Trust
U.S. citizenship required
Successful completion of background investigations as required by the government customer
Preferred / Desired Qualifications
Experience with cloud platforms (AWS, Azure) including GovCloud environments
Knowledge of FedRAMP or government compliance requirements
Experience with monitoring tools (Prometheus, Grafana, ELK stack)
Familiarity with service mesh technologies (Istio, Linkerd)
Experience with GitOps workflows and tools (ArgoCD, Flux)
Knowledge of secrets management and PKI (Vault, cert-manager)
Experience in aviation, defense, or government program environments
Experience with developer portal implementation (Backstage or equivalent) and platform documentation
Desired but not required: Commutable distance (1 hour or less) to Gaithersburg, MD; Eagan, MN; or Egg Harbor Township, NJ.
Why Leidos?
You’ll work on systems where performance, precision, and reliability matter — every second. This is not experimental AI for prototypes. This is disciplined, responsible AI applied to mission-critical software that supports national infrastructure.
If you’re excited by solving complex problems in regulated, real-world environments — and using AI as a force multiplier rather than a shortcut — we’d like to talk.
ATMC
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:
September 18, 2026For 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 $87,100.00 - $157,450.00The 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.
