Artificial Intelligence Engineer

L3Harris Technologies•Camden, NJ

1d•$109,500 - $203,500•Onsite

About The Position

L3Harris is seeking a Forward Deployed Engineer of AI Platforms to support the Space and Mission Systems (SMS) segment AI organization. The role builds, deploys, and maintains secure Linux, container, and cloud infrastructure supporting AI-enabled applications across approved enterprise and government environments. It requires hands-on platform engineering experience, particularly with Red Hat Enterprise Linux (RHEL), containerized applications, and cloud deployment. AWS GovCloud experience is strongly preferred, and comparable Azure Government experience is valued. The engineer works with AI application developers and cybersecurity personnel to automate deployments, maintain secure configurations, resolve vulnerabilities, and support system assessment and authorization activities. The job is located in Camden, New Jersey, follows a 9/80 schedule with every other Friday off, and may require travel up to 20% of the time.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, or a related technical field and at least 6 years of prior relevant experience; or a graduate degree and at least 4 years of prior related experience.
Hands-on experience administering RHEL or closely related enterprise Linux environments.
Experience building, deploying, and maintaining containerized applications using Podman or Docker.
Programming or scripting proficiency, with Python preferred, and experience automating deployment or operational tasks.
Hands-on experience deploying or operating workloads in AWS, Azure, or a comparable cloud environment.
Experience with Git-based workflows and CI/CD pipelines.
Working knowledge of system hardening, patching, vulnerability remediation, and configuration management; familiarity with DISA STIGs.
Strong troubleshooting, documentation, and communication skills.
Ability to obtain and maintain a DoD Secret clearance.

Nice To Haves

Hands-on experience with AWS GovCloud (US), Azure Government, or comparable government cloud environments.
Experience supporting DCSA-authorized classified systems or other government-authorized environments, including RMF, security assessments, and ATO sustainment.
Experience with Red Hat OpenShift, Kubernetes, infrastructure automation, or configuration-as-code practices.
Experience with container registries and artifact repositories such as JFrog Artifactory.
Experience deploying or integrating LLMs, local model-serving infrastructure, RAG components, or other AI-enabled applications.
Experience delivering software or infrastructure in defense, aerospace, or other regulated, mission-critical environments.

Responsibilities

Deploy, operate, and troubleshoot containerized AI applications and supporting services in approved cloud and on-premises environments.
Administer RHEL-based systems, including patching, access controls, configuration management, monitoring, and system hardening.
Build and maintain container images using Podman or Docker; manage artifacts and registries; support vulnerability scanning, SBOM generation, and remediation.
Automate infrastructure configuration and application deployment using scripting, Git-based workflows, and CI/CD pipelines.
Apply applicable DISA STIG requirements and work with cybersecurity personnel to document configurations, address findings, and support government assessment, authorization, and ATO sustainment activities.
Integrate and maintain approved AI services, including model-serving and retrieval components, in collaboration with application and data teams.
Maintain deployment procedures, operational documentation, and technical records using tools such as Jira and Confluence.
Travel up to 20% of the time.