AI / Automation Engineer (US Citizens)
Prolim Global
Job Title : AI / Automation Engineer (AI Software Engineer 2)
Location : Chandler, AZ 85286
Pay Range : 100 - 105/hr. W2
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
$60 - $64 per hour
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