Job description

Chipton-Ross is seeking multiple AI/Automation Engineer 2's for a contract opportunity in Chandler, AZ. BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE): o 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. o Must have the ability to obtain and maintain a U.S. Government DoD Secret security clearance. o 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. o Experience integrating APIs, LLM services, and agent orchestration frameworks into applications or operational workflows. Experience with LangChain, Mastra, or comparable toolchains is welcome. o Experience with Docker or comparable container technologies is required. Experience with orchestration platforms such as Kubernetes or OpenShift is beneficial. o Experience developing, hosting, or supporting AI/ML applications in on-premise containerized environments; cloud-based deployment experience is also valued. o Hands-on experience working in Linux environments, including scripting and system configuration. o Proficiency in Python or Go (Golang) with a strong background in software development, debugging, and testing. o Experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases. o Strong working understanding of LLM deployment considerations, including hosting, inference, and operational reliability. POSITION RESPONSIBILITIES: We are seeking a highly motivated AI / Automation Engineer to join our dynamic team. In this role, you will design, develop, deploy, and support AI-enabled automation solutions that integrate existing LLM and agentic capabilities into engineering and infrastructure workflows. The role emphasizes bringing AI-enabled tools into operational use in on-premise and classified environments. This role sits at the intersection of AI, automation, CI/CD, and infrastructure, giving you the opportunity to: o Build and integrate AI-enabled automation capabilities into engineering workflows. o Deploy and support LLM-enabled, agentic, and RAG-based solutions. o Enable reliable delivery through containerization, CI/CD, and infrastructure support. In this role, you will: o Design, develop, document, test, and debug AI-enabled automation capabilities that integrate existing LLM services, APIs, and engineering tools into operational workflows. o Build, deploy, and support agent orchestration frameworks and Retrieval-Augmented Generation (RAG) solutions, including integrations with vector databases and enterprise data sources. o Support containerized, on-premise and classified environments at scale, with cloud-based deployment exposure also valued. o Troubleshoot deployed AI and automation solutions, resolve integration and performance issues, and improve observability, availability, and maintainability over time. o Develop, deploy, and maintain containerized applications using Docker or comparable container technologies, with attention to load balancing, virtual-machine resource utilization, and system performance. o Build and maintain CI/CD pipelines, version-control practices, and automated deployment workflows that enable reliable delivery of AI-enabled tools and services. o Partner with software, DevOps, infrastructure, and mission stakeholders to identify automation opportunities and transition solutions into production use. o Provide infrastructure support by resolving container, system-performance, resource-utilization, and availability issues that affect deployed solutions. o Communicate clearly with technical and non-technical stakeholders, both in writing and verbally. o Perform other related duties as assigned. PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE): o 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 REQUIRED EDUCATION: Bachelor's Degree is required. School must be accredited. WORK HOURS: 9/80. On-site in Chandler, AZ. MISCELLANEOUS: Applicants responding to this position will be subject to a government security investigation and must meet eligibility requirements by currently possessing the ability to view classified government information.

Requirements

Must-haves

Chipton-Ross is seeking multiple AI/Automation Engineer 2's for a contract opportunity in Chandler, AZ.
BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):
o 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.
o Must have the ability to obtain and maintain a U.S. Government DoD Secret security clearance.
o Experience integrating APIs, LLM services, and agent orchestration frameworks into applications or operational workflows. Experience with LangChain, Mastra, or comparable toolchains is welcome.
o Experience with Docker or comparable container technologies is required. Experience with orchestration platforms such as Kubernetes or OpenShift is beneficial.
o Experience developing, hosting, or supporting AI/ML applications in on-premise containerized environments; cloud-based deployment experience is also valued.
o Hands-on experience working in Linux environments, including scripting and system configuration.
o Proficiency in Python or Go (Golang) with a strong background in software development, debugging, and testing.
o Experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases.
o Strong working understanding of LLM deployment considerations, including hosting, inference, and operational reliability.
This role sits at the intersection of AI, automation, CI/CD, and infrastructure, giving you the opportunity to:
o Build and integrate AI-enabled automation capabilities into engineering workflows.
o Deploy and support LLM-enabled, agentic, and RAG-based solutions.
o Enable reliable delivery through containerization, CI/CD, and infrastructure support.
o Design, develop, document, test, and debug AI-enabled automation capabilities that integrate existing LLM services, APIs, and engineering tools into operational workflows.
o Build, deploy, and support agent orchestration frameworks and Retrieval-Augmented Generation (RAG) solutions, including integrations with vector databases and enterprise data sources.
o Support containerized, on-premise and classified environments at scale, with cloud-based deployment exposure also valued.
o Troubleshoot deployed AI and automation solutions, resolve integration and performance issues, and improve observability, availability, and maintainability over time.
o Develop, deploy, and maintain containerized applications using Docker or comparable container technologies, with attention to load balancing, virtual-machine resource utilization, and system performance.
o Build and maintain CI/CD pipelines, version-control practices, and automated deployment workflows that enable reliable delivery of AI-enabled tools and services.
o Partner with software, DevOps, infrastructure, and mission stakeholders to identify automation opportunities and transition solutions into production use.

Nice-to-haves

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):
o 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

Application prep

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Keywords to mirror

aillmdockerkubernetesmlpythongogolangci/cd

Platform: careers-page
Effort: medium

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