Lead, Software Engineer

L3Harris•Rochester, FL

About The Position

L3Harris Technologies is seeking a Senior DevSecOps Engineer to modernize and scale secure software delivery for mission-focused programs within its Space Systems sector. The role partners with software, cybersecurity, infrastructure, and program teams to build reliable engineering platforms, automate secure delivery pipelines, and improve developer productivity across hybrid cloud and on-premises environments. It calls for hands-on DevSecOps experience, continuous improvement, and practical use of technologies such as infrastructure as code, container platforms, automated security controls, observability tooling, and AI-assisted engineering workflows. The position also develops and improves AI services, APIs, workflow components, and agentic workflows for AI-assisted remediation and engineering automation. It applies secure-by-default patterns and designs AI tool and workflow practices that support reliability, traceability, auditability, and safe execution. The role improves testing, evaluation, observability, and runtime diagnostics for AI-enabled workflows, and mentors peers while promoting a collaborative DevSecOps culture focused on quality, security, and continuous improvement. The role is based in Chantilly, Virginia; Melbourne, Florida; or Rochester, New York. Its 9/80 schedule consists of working 9 out of every 14 days for 80 hours, with every other Friday off.

Requirements

Active TS/SCI clearance with CI Polygraph.
Bachelor’s degree and at least 9 years of prior relevant experience; or a graduate degree and at least 7 years of prior related experience; or, in lieu of a degree, at least 13 years of prior related experience.
Experience supporting CI/CD, build, release, test automation, platform engineering, systems engineering, or DevOps functions in a software environment.
Experience with one or more scripting or programming languages such as Python, Bash, PowerShell, or Java.
Experience with one or more source control and CI/CD platforms such as GitLab, Jenkins, GitHub, Bitbucket, Azure DevOps, or Bamboo.
Experience with Linux administration and/or cloud-hosted environments.
Experience with at least one modern automation approach, such as infrastructure as code, configuration management, containerization, or orchestration.
Experience troubleshooting technical issues and collaborating across software, infrastructure, operations, and security teams.
Experience with AI-enabled automation, AI-assisted software delivery, ML platform support, or integrating AI/ML services into engineering workflows.

Nice To Haves

Experience with MCP-based integrations, agent frameworks, orchestration patterns, or AI tool-execution systems.
Experience with application or supply-chain security practices such as SAST, SCA, container scanning, SBOM generation, secrets management, or policy-as-code.
Experience with container and platform technologies such as Docker, Kubernetes, OpenShift, AWS, or GovCloud.
Experience with observability, telemetry, or evaluation pipelines for AI-enabled systems.
Experience with infrastructure as code or automation approaches such as Terraform, Ansible, or Helm.
Experience working in Agile or Scrum environments and collaborating across software, cyber, operations, and infrastructure teams.
Experience supporting classified, regulated, or mission-critical environments.

Responsibilities

Design, implement, and improve DevSecOps pipelines for build, test, security, release, and deployment activities.
Standardize and automate the software development lifecycle across development, integration, and production-like environments.
Support cloud and on-premises platform operations, including deployment automation, troubleshooting, patching, and reliability improvements.
Integrate security into delivery workflows through automated scanning, policy checks, secrets handling, and secure-by-default practices.
Work with development teams to improve build stability, release quality, deployment consistency, and feedback cycles.
Contribute to infrastructure as code, configuration management, and repeatable environment provisioning.
Implement logging, monitoring, and operational visibility solutions to improve system health, diagnostics, and incident response.
Evaluate and apply practical technologies, including AI-assisted automation, to reduce manual effort and improve team efficiency.
Design, implement, and improve AI services, APIs, and workflow components that support AI-assisted remediation and engineering automation.
Develop and mature agentic workflows that combine LLM reasoning, tool use, enterprise integrations, and policy guardrails for engineering and security use cases.
Design prompt, tool, and workflow patterns that improve reliability, traceability, auditability, and safe execution of AI-assisted actions.
Implement secure-by-default service patterns, including input validation, access control, secrets handling, structured logging, and least-privilege integration behavior.
Collaborate with software, cyber, infrastructure, and program teams to translate mission needs into practical AI-enabled engineering capabilities.
Improve testing, evaluation, observability, and runtime diagnostics for AI service workflows, tool interactions, and model-assisted outputs.
Mentor peers and promote a collaborative DevSecOps culture focused on quality, security, and continuous improvement.