The Lockheed Martin Artificial Intelligence Center (LAIC) is seeking an experienced infrastructure and platform engineer to help build and operate the AI Factory, an enterprise platform for developing, deploying, and running artificial intelligence and machine learning (AI/ML) capabilities.
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
• 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.
• 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.
Pay Information
GeoZone Definition: GeoZones are geographic groupings created by Lockheed Martin to align compensation ranges with regional labor markets and cost-of-labor differences across the United States. Locations are assigned a Geo Zone based on the primary work location of the role.
- Full-time salary range (GEOZONE 1): $150800.00 - $280000.00
- Includes metropolitan areas such as Sunnyvale CA; Pal Alto, CA; New York City metropolitan area; Newark, New Jersey; etc.
- Full-time salary range (GEOZONE 2): $135700.00 - $251900.00
- Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.
- Full-time salary range (GEOZONE 3): $120600.00 - $224000.00
- Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.
- Full-time salary range (GEOZONE 4): $108600.00 - $201600.00
- Includes metropolitan areas such as Camden, AR; Lexington, KY; Lufkin, TX; etc.
At Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow—both professionally and personally.
The salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only.
Lockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer.
Benefits offered: Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.
- Annual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.
- For (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.
Skills Required
- Professional experience developing infrastructure or platform automation with 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
- 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 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
Lockheed Martin Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lockheed Martin and has not been reviewed or approved by Lockheed Martin.
-
Retirement Support — Retirement benefits are described as a standout element, with a strong 401(k) program and options like an employee stock purchase plan. Feedback suggests these features meaningfully enhance total compensation and long‑term financial security.
-
Healthcare Strength — Healthcare coverage is portrayed as comprehensive from day one, with multiple plan options, mental health resources, and virtual care. Wellness supports such as on‑site services and preventive programs are also highlighted.
-
Flexible Benefits — Work arrangements often include compressed schedules and telework, contributing to a favorable work‑life balance. Feedback suggests this flexibility is a key reason many view the overall package positively.
Lockheed Martin Insights
What We Do
Customer Focus, Innovation and Purpose are Built Into Everything We Do. Lockheed Martin. Your Mission is Ours ™. Headquartered in Bethesda, Maryland, Lockheed Martin is a global security and aerospace company principally engaged in the research, design, development, manufacture, integration and sustainment of advanced technology systems, products and services.
