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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.
- 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.