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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Systems Engineer Stf - **Company:** Lockheed Martin - **Location:** New York, NY, United States (Remote available) - **Experience:** Experienced - **Salary:** $150,800.0 - $280,000.0 - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Application Programming Interfaces (APIs), Artificial Intelligence, Bash Shell, Configuration Management, Cyber Security, Computer Programming, Continuous Integration, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Linux System Administration, Octopus Deploy, OpenShift, Software Maintenance, Ansible, Prometheus, Subsystems, System Testing, Systems Integration, Workflow Management Systems, Curam Configuration Tools, Scripting, Cloud Platform System, High Performance Computing, Delivery Pipeline, Grafana, Gitlab-ci, Integration Tests, Kubernetes, Infrastructure Automation Frameworks, Rancher, Machine Learning Operations, Hardware Infrastructure, Terraform, Golang - **Published:** October 8, 2026 - **Apply:** https://dejobs.org/x/x/2938BF4E65874740A223ADFD833B7617/job/ ## About the Role * Professional experience developing infrastructure or platform automation, including substantial hands-on programming or scripting in Python, Go, Bash, or a similar language. * Experience designing and maintaining CI/CD pipelines and automating software or infrastructure deployments. * Experience with Kubernetes, containers, and Linux-based systems. * Experience using infrastructure-as-code or configuration-management tools. * Strong written and verbal communication skills. * US citizenship is required due to system access. Desired Skills * Experience with GitOps and pipeline tools such as Argo CD, Tekton, or GitLab CI/CD. * Experience with Kubernetes packaging and configuration tools such as Helm or Kustomize. * Experience with Terraform, Ansible, or comparable automation tools. * Experience building internal developer platforms, self-service tools, APIs, or reusable deployment frameworks. * Experience with observability tools such as Prometheus, Grafana, and Thanos. * Familiarity with container security, image registries, and software supply-chain practices. * Experience with Kubernetes storage, including Container Storage Interfaces and persistent volumes. * Experience with platforms such as OpenShift, Rancher, or Google Kubernetes Engine. * Familiarity with GPU computing, high-performance computing, or AI/ML orchestration tools such as Kubeflow or OpenDataHub. * Experience deploying services in on-premises, isolated, or cloud environments. ## Description In this role, you will develop the automation, tooling, and platform capabilities that make AI/ML environments reliable, repeatable, and easier for teams to use. You will work alongside platform engineers, software engineers, product managers, data scientists, Central IT, Cybersecurity, and other engineering teams. Your responsibilities will include the following: * Designing, developing, testing, and maintaining software and automation for platform provisioning, configuration, deployment, and operations. * Building and improving CI/CD and GitOps workflows that deliver infrastructure and platform services consistently and securely. * Developing infrastructure as code, reusable tooling, and self-service capabilities that reduce manual work and improve developer experience. * Operating and improving Kubernetes-based environments used to train, deploy, and run AI/ML systems. * Improving platform reliability through observability, automated validation, incident response, and durable fixes to recurring problems. * Working with cybersecurity and partner teams to incorporate security controls into development and deployment workflows. * Reviewing designs and code, guiding technical decisions, and mentoring other engineers. * Collaborating with users and vendors to identify platform needs and deliver practical improvements. As a mid-level engineer, you'll be a strong fit for this role if you have a solid track record of technical expertise and a growing ability to apply strategic thinking to complex problems. You're able to prioritize tasks, manage multiple projects, and collaborate effectively with internal stakeholders. You should be comfortable diagnosing distributed-system issues and balancing delivery speed with reliability and security. Responsible for autonomy hardware and software system integration and testing including verification and validation.Translates customer requirements into product and systems specifications while addressing technical, schedule, and cost considerations; Establishes functional and technical specifications and standards for autonomous systems; Determines sensing hardware components; Recommends and selects appropriate control systems; Integrates and optimizes the autonomous compute and sensing hardware and software; Solves hardware/software interface problems; Develops plan(s) to integrate autonomous functionality into product(s) and platform(s) and other system(s); Develops test plans for validation and verification and procedures for test and evaluation requirements in collaboration with designers and developers; Performs integration testing and coordinates subsystem and/or system testing activities for autonomous programs; Documents and conducts analysis of test results and recommends fixes to software, hardware components, subsystems and systems; Interfaces with other teams involved the development lifecycle for perception