Description

Job Description -

Our client Northrop Grumman’s Space Sector invites you to bring your pioneering spirit to our collaborative teams. As an AI / Automation Engineer – Level 2 in Chandler, AZ, you’ll be a key contributor to missions of national importance, helping define what’s possible from day one. This position is 100% onsite and cannot accommodate telecommute work.

This role sits at the intersection of AI, automation, CI/CD, and infrastructure, giving you the opportunity to:

Build and integrate AI-enabled automation capabilities into engineering workflows
Deploy and support LLM-enabled, agentic, and RAG-based solutions
Enable reliable delivery through containerization, CI/CD, and infrastructure support
In this role, you will:

Design, develop, document, test, and debug AI-enabled automation capabilities that integrate existing LLM services, APIs, and engineering tools into operational workflows.
Build, deploy, and support agent orchestration frameworks and Retrieval-Augmented Generation (RAG) solutions, including integrations with vector databases and enterprise data sources.
Support containerized, on-premise and classified environments at scale, with cloud-based deployment exposure also valued.
Troubleshoot deployed AI and automation solutions, resolve integration and performance issues, and improve observability, availability, and maintainability over time.
Develop, deploy, and maintain containerized applications using Docker or comparable container technologies, with attention to load balancing, virtual-machine resource utilization, and system performance.
Build and maintain CI/CD pipelines, version-control practices, and automated deployment workflows that enable reliable delivery of AI-enabled tools and services.
Partner with software, DevOps, infrastructure, and mission stakeholders to identify automation opportunities and transition solutions into production use.
Provide infrastructure support by resolving container, system-performance, resource-utilization, and availability issues that affect deployed solutions.
Communicate clearly with technical and non-technical stakeholders, both in writing and verbally.
Perform other related duties as assigned.
Basic Qualifications for Level 2:

Bachelor’s degree with 2 years of professional experience – OR – Master’s degree with 1 years of professional experience – OR – PhD with 1 year of professional experience.
Must have the ability to obtain and maintain a U.S. Government DoD Secret security clearance.
Hands-on experience integrating and deploying LLM-enabled applications, including model hosting, agentic workflows, RAG, and inference considerations. Experience with advanced fine-tuning and inference optimization is preferred and may be developed in the role
Experience integrating APIs, LLM services, and agent orchestration frameworks into applications or operational workflows. Experience with LangChain, Mastra, or comparable toolchains is welcome
Experience with Docker or comparable container technologies is required. Experience with orchestration platforms such as Kubernetes or OpenShift is beneficial
Experience developing, hosting, or supporting AI/ML applications in on-premise containerized environments; cloud-based deployment experience is also valued
Working knowledge of CI/CD, version control, automated deployment practices, and infrastructure fundamentals. Experience with tools such as GitLab, Jenkins, or similar platforms is preferred
Hands-on experience working in Linux environments, including scripting and system configuration.
Proficiency in Python or Go (Golang) with a strong background in software development, debugging, and testing.
Experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases.
Strong working understanding of LLM deployment considerations, including hosting, inference, and operational reliability

Key Skills

Education

Any Graduate