AI Applications Developer

S R International•Phoenix, AZ

1d•Hybrid

About The Position

The State of Arizona’s Arizona Department of Economic Security, Division of Technology Services, is seeking a Senior/Lead AI Applications Developer to identify, design, and implement AI solutions that reduce administrative workload and improve operational efficiency. The developer will work with business and technology teams to translate operational requirements into technical specifications, evaluate enterprise AI tools such as Google Gemini and NotebookLM, and develop secure custom AI applications within the DTS closed environment. The role involves hands-on AI and LLM application development, including Generative AI, prompt engineering, RAG architectures, AI agents, embeddings, vector databases, and foundation models. The developer will implement security controls, content safety, guardrails, and Responsible AI practices, assess outputs for bias, hallucinations, reliability, and security vulnerabilities, and maintain documentation for code, architecture, system prompts, and workflows. The position is hybrid and limited to local Phoenix candidates. It is contract-to-hire, and candidates must be eligible for FTE conversion. The State of Arizona cannot sponsor visas. A valid Level One Fingerprint Clearance Card and HireRight background check, including Global ID facial biometrics, are required.

Requirements

Master’s degree in AI or at least 2 years of AI development experience.
The posting also states an education/experience requirement of a bachelor’s degree plus 10 or more years of programming and analysis experience, or equivalent experience.
Experience gathering and translating business requirements into technical specifications.
Hands-on experience with AI/LLMs, Generative AI, prompt engineering, and RAG architectures.
Experience designing, prototyping, and deploying custom AI applications.
Understanding of LLMs, embeddings, vector databases, and AI agents.
Knowledge of AI governance, data privacy, security, and Responsible AI principles.
Experience evaluating AI outputs for bias, hallucinations, and security vulnerabilities.
Ability to document application architecture, code, system prompts, and workflows.
Strong communication, analytical, and problem-solving skills.
Must be a local Phoenix, Arizona candidate and comfortable working in the DTS closed environment.
Must be eligible for FTE conversion; the State of Arizona cannot sponsor visas.
Must obtain and maintain a valid Level One Fingerprint Clearance Card under Arizona Revised Statute 41-1969.
Must complete a HireRight background check and Global ID facial biometrics.

Nice To Haves

Azure OpenAI and Azure AI Foundry.
Python programming.
C# and .NET Framework.
SQL and database technologies.
Google Cloud, Vertex AI, and the Gemini ecosystem.
GitHub Copilot and AI-assisted development tools.
RAG pipelines, AI agents, and foundation model fine-tuning.
Azure AI Content Safety, guardrails, and Responsible AI Dashboard.
MLOps, CI/CD, AI governance, and automated testing.
Agile development methodology.
Master’s degree preferred.

Responsibilities

Identify and implement AI solutions to reduce administrative workload and improve operational efficiency.
Gather business requirements and translate operational processes into technical specifications.
Evaluate enterprise AI tools, including Gemini and NotebookLM, against custom AI development options.
Architect, prototype, and deploy custom AI applications within the DTS closed environment.
Develop secure AI solutions using Python and approved enterprise AI platforms such as Vertex AI.
Build and optimize RAG pipelines, apply advanced prompt engineering, and integrate AI agents.
Work with LLMs, embeddings, vector databases, and foundation models.
Implement AI security controls, content safety, guardrails, and Responsible AI practices.
Evaluate AI outputs for bias, hallucinations, reliability, and security vulnerabilities.
Maintain technical documentation covering code, architecture, system prompts, and workflows.
Use GitHub Copilot and other approved AI coding tools to improve development productivity.
Collaborate with operational teams, stakeholders, and technical teams to deliver AI solutions.