AI Software Engineer II

Mavensoft Technologies, LLC; Chandler (AZ); On-site; USD 120,000 - 160,000; Full time

Job summary

Mavensoft Technologies, LLC in Chandler, AZ seeks an AI Software Engineer II to design, develop, and deploy AI-enabled automation that integrates LLM services and enterprise tools in operational workflows. This onsite role requires strong Python or Go skills and hands-on experience with Docker, Kubernetes, and RAG pipelines.

You will build agent orchestration frameworks, support on-premises and cloud deployments, and collaborate with DevOps and mission stakeholders to ensure reliability,

Qualifications

• BS/MS/PhD with DoD Secret clearance eligibility.
• Experience deploying LLM-enabled apps and RAG pipelines.
• Proficient in Python or Go for software development.
• Experience with Docker/Kubernetes/OpenShift.
• CI/CD tooling (GitLab, Jenkins) and Linux scripting.

Responsibilities

• Design and develop AI-enabled automation integrating LLMs and APIs.
• Build agent orchestration frameworks and RAG solutions.
• Support on-prem and cloud deployments in secure environments.
• Troubleshoot performance and improve observability and reliability.
• Develop and maintain CI/CD pipelines and deployment workflows.
• Collaborate with DevOps, infrastructure, and mission stakeholders.

Skills

Design and development of AI-enabled运

Education

Bachelor’s degree with 2 years experience

Master’s degree with 1 year experience

PhD with 1 year experience

Tools

Docker

Kubernetes

OpenShift

LangChain

Mastra

GitLab

Jenkins

Job description

Tittle :AI Software Engineer II

Work Location:Onsite in Chandler, AZ
Duration:12 months
Terms:W2 Contract
Work Authorization:US Citizen; must have the ability to obtain/maintain a Secret security clearance
Responsibilities:

• 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-premises 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 containers, 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.

Required Qualifications:

• Bachelor’s degree with 2 years of professional experience;
• OR a Master’s degree with 1 year of professional experience;
• OR a 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.