AI​/Automation Engineer - Level 2; Chandler); AHT

No relocation assistance available

CLEARANCE REQUIRED FOR START:
No

CLEARANCE TYPE:
None

TRAVEL:
Yes, 10% of the Time

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.

Expand your horizons, advance your career, and contribute to a secure future for generations to come. 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.

We are seeking a highly motivated AI / Automation Engineer to join our dynamic team. In this role, you will design, develop, and maintain automation solutions that impact engineering and infrastructure across the organization. You will combine hands-on software engineering with cutting-edge AI and ML to automate engineering, Dev Ops, infrastructure tasks, processes, and workflows.

• Build and integrate AI-powered capabilities into engineering workflows
• Design and operate robust CI/CD Dev Ops pipelines
• Support containerized, cloud and on-premise environments at scale

Join us and be part of a team driving innovative solutions at the forefront of space systems and advanced software.

In this role, you will:

• Design, develop, document, test, and debug AI and ML capabilities to automate engineering and infrastructure workflows.
• Automate processes by building and maintaining CI/CD pipelines and AI-enabled tooling within a Dev Ops environment.
• Build and maintain agent orchestration frameworks that integrate with LLM services, system services, and engineering tools.
• Develop, deploy, and maintain containerized applications (e.g., Docker, Kubernetes) to ensure portability, scalability, and reliability.
• Implement and support RAG pipelines and vector database integrations to enable intelligent retrieval and decision-making.
• Provide infrastructure support by troubleshooting issues, optimizing performance, and maintaining high availability and observability of systems.
• Collaborate closely with engineering, Dev Ops, and infrastructure teams to identify automation opportunities and bring them to production.
• Communicate clearly with technical and non-technical stakeholders, both in writing and verbally.
• Perform other related duties as assigned.

If this job description reads like it was written specifically for you, we'd like to talk with you.

• 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 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 CI/CD, version control systems, and automated pipelines for application deployment.
• Experience developing and deploying AI and/or Machine Learning (ML) capabilities.
• Experience with APIs and integrating models into applications or agentic frameworks ( e.g. Mastra, Lang Chain, or similar toolkits) for building autonomous agents.
• Experience developing and hosting AI/ML models in cloud-based environments (e.g., AWS, Azure) and/or on-premise containerized infrastructure.
• Experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases.
• Strong understanding of Large Language Models (LLMs), including concepts such as fine-tuning, hosting,…