AI Software Engineer II
About The Position
The AI Software Engineer II designs, develops, documents, tests, and debugs AI-enabled automation capabilities by integrating existing LLM services, APIs, and engineering tools into operational workflows. The role builds, deploys, and supports agent orchestration frameworks and Retrieval-Augmented Generation (RAG) solutions, including integrations with vector databases and enterprise data sources. The engineer supports containerized on-premises and classified environments at scale, with cloud-based deployment exposure also valued. The role troubleshoots deployed AI and automation solutions, resolves integration and performance issues, and improves observability, availability, and maintainability. It also develops and maintains containerized applications and CI/CD workflows, supports infrastructure issues affecting deployed solutions, and collaborates with software, DevOps, infrastructure, and mission stakeholders to bring automation solutions into production. The position is onsite in Chandler, Arizona, for a 12-month W2 contract. The candidate must be able to obtain and maintain a U.S. Government DoD Secret security clearance.
Requirements
- 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.
- 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 integrating APIs, LLM services, and agent orchestration frameworks into applications or operational workflows.
- Experience with Docker or comparable container technologies.
- Experience developing, hosting, or supporting AI/ML applications in on-premises containerized environments.
- Working knowledge of CI/CD, version control, automated deployment practices, and infrastructure fundamentals.
- 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 RAG pipelines and vector databases.
- Strong working understanding of LLM deployment considerations, including hosting, inference, and operational reliability.
Nice To Haves
- Experience with advanced fine-tuning and inference optimization; these skills may also be developed in the role.
- Experience with LangChain, Mastra, or comparable toolchains.
- Experience with orchestration platforms such as Kubernetes or OpenShift.
- Cloud-based deployment experience.
- Experience with GitLab, Jenkins, or similar platforms.
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 RAG solutions, including integrations with vector databases and enterprise data sources.
- Support containerized, on-premises, and classified environments at scale; cloud-based deployment exposure is also valued.
- Troubleshoot deployed AI and automation solutions, resolve integration and performance issues, and improve observability, availability, and maintainability.
- Develop, deploy, and maintain containerized applications using Docker or comparable technologies, considering load balancing, virtual-machine resource utilization, and system performance.
- Build and maintain CI/CD pipelines, version-control practices, and automated deployment workflows for 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.
- Resolve container, system-performance, resource-utilization, and availability issues affecting deployed solutions as part of infrastructure support.
- Communicate clearly in writing and verbally with technical and non-technical stakeholders.
- Perform other related duties as assigned.
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What This Job Offers
Career Level
Mid Level
