- Salary
- $172k – $258k
- Location
- CARBR2, United States of America
- Type
- Full-time
- Department
- Engineering
- Education
- PhD
- Clearance
- Required
- Source
- Workday
Description
Description
At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history.Northrop Grumman's Space Sector is seeking an AI/DevOps Engineer - Level 4 to support the deployment, integration, and sustainment of AI/ML and LLM-enabled tools in secure enterprise environments in Redondo Beach, CA.
*Please be aware that this position is contingent upon obtaining and maintaining associated business and/or customer funding and obtaining final clearances and program access(es) within a reasonable period of time as determined by the company. Continued employment thereafter will be subject to maintenance at the level of clearance and program access required for the position in the future.
In this role, you will focus on Linux-based infrastructure, containerized deployments, cloud platforms, automation, and secure application integration in support of operational AI capabilities. You will serve as a technical contributor across software, platform, AI/ML, and cybersecurity teams to deliver scalable, maintainable, and secure solutions. The role requires independent execution, strong troubleshooting skills, and the ability to support complex deployments in enterprise environments.
Responsibilities include, but are not limited to, the following:
- Deploy, configure, and sustain infrastructure supporting AI/ML and LLM-enabled applications and services.
- Administer and troubleshoot Linux-based environments across development, test, and production.
- Build, deploy, and manage containerized solutions using technologies such as Podman, Docker, Portainer, and Kubernetes.
- Develop automation and operational tooling using Bash and Python.
- Support cloud-based deployments and integrations in AWS and/or Azure environments.
- Implement and maintain source control and CI/CD workflows using GitHub and/or GitLab.
- Configure and troubleshoot enterprise integrations involving proxies, firewalls, SSL certificates, OAuth, SSO, credential management, and session management.
- Partner with cross-functional teams to resolve technical issues and improve the reliability, security, and maintainability of AI platform capabilities.
- Develop and maintain technical documentation, deployment procedures, and operational runbooks.
Basic Qualifications:
- Bachelor’s degree in a STEM discipline with 8 years of relevant experience; OR Master’s degree in STEM with 6 years of relevant experience; OR PhD in STEM with 4 years of relevant experience
- Must have an active U.S. Government Top Secret clearance at the time of application
- Experience operating and troubleshooting Linux environments
- Experience developing automation using Bash and Python
- Experience deploying and managing containerized applications using Podman, Docker, Portainer, Kubernetes, or similar technologies
- Experience deploying, supporting, or sustaining AI/ML, LLM-enabled, or other advanced software solutions in production or enterprise environments
- Experience with AWS and/or Azure cloud platforms
- Experience with GitHub and/or GitLab
- Experience with OAuth/SSO, credential management, and session management
- Experience working with SSL certificates and enterprise proxy/firewall configurations
Preferred Qualifications:
- Experience with Ollama, SageMaker, Azure AI Foundry, or similar model deployment technologies
- Experience with LangChain, Langflow, MCP, Supergateway, or similar AI orchestration tooling
- Experience with Keycloak or similar identity and access management platforms
- Experience with MLOps tools and practices such as MLflow, Kubeflow, Airflow, model registries, and automated deployment workflows.
- Familiarity with Java
- Familiarity with VS Code and/or Eclipse IDE
- Experience supporting AI inference services, APIs, microservices, or batch processing pipelines in enterprise environments