AI Applications Developer

AI Applications Developer

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6 Months (Contract to Hire)-W2 only

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Phoenix, AZ Hybrid

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Local Only. This is a contract to hire position.

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Bachelor's degree plus 10 or more years of programming and analysis experience (or equivalent experience). Master's Degree preferred.

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The Applications Developer Senior/Lead is responsible for identifying and implementing Artificial Intelligence (AI) solutions to decrease administrative workload and improve quality. Acting as a bridge between operational units and technology, this role collaborates with diverse teams to integrate approved AI tools and develop secure, custom solutions within the Division of Technology Services (DTS) closed environment. The Applications Developer Senior/Lead translates operational processes into detailed technical specifications, determining whether to leverage existing enterprise software (e.g., Gemini, NotebookLM) or build bespoke local solutions. This role focuses heavily on technical architecture and AI development by designing, prototyping, and deploying custom AI tools from scratch within the DTS environment. This position maintains comprehensive technical documentation of code, architecture, and system prompts.

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Translate complex operational processes and business needs into detailed technical specifications and actionable requirements for AI implementation. Determine whether to leverage existing enterprise software or build bespoke local solutions.

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Architect, prototype, and deploy custom AI tools from scratch within the DTS closed environment. Utilize programming languages common in AI development (e.g., Python) and leverage approved enterprise AI platforms (e.g., Google Cloud/Vertex AI, Gemini ecosystems).

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Act as a bridge between operational units and technology to recommend and guide the adoption of already-approved agency AI tools (e.g., Gemini, NotebookLM) to solve immediate operational challenges and decrease administrative workload.

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Apply hands-on experience working with AI/LLMs, advanced prompt engineering, and retrieval-augmented generation (RAG) architectures to develop and refine secure, high-quality custom solutions.

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Maintain comprehensive, up-to-date technical documentation of code, architecture, system prompts, and workflows to ensure security and compliance within the DTS closed environment.

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- Multiple programming languages, multiple database management systems, multiple development platforms, and systems integration - Software development processes including analysis, design, coding, system and user testing, problem resolution and planning - Agile Development Methodology - Microsoft Responsible AI Standard: Deep understanding of Microsoft's six core AI principles: Fairness, Reliability and Safety, Privacy and Security, Inclusiveness, Transparency, and Accountability. - Azure Cloud Architecture: Understanding how compute, storage, and networking choices influence AI solution design within Azure, including familiarity with Azure AI Foundry. - Generative AI Mechanics: Comprehension of Large Language Models (LLMs), embeddings, vector databases, and how foundation models (like GPT-4o) process and generate information. - MLOps & AI Governance: Knowledge of the end-to-end machine learning lifecycle, continuous integration/continuous deployment (CI/CD) for AI, and compliance frameworks for data privacy.

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- Written and verbal communication - Strong problem solving, priority setting, multi-tasking, analytical, and collaboration skills - AI/LLMs, prompt engineering, and retrieval-augmented generation (RAG) - Utilizing approved enterprise AI platforms (e.g., Google Cloud/Vertex AI, Gemini ecosystems) - Programming & Frameworks: Proficiency in Python, SQL, and C# (.NET Framework). - Azure OpenAI Implementation - Building Retrieval-Augmented Generation (RAG) pipelines, advanced prompt engineering, fine-tuning foundation models, and integrating AI agents. - Configuring Azure AI Content Safety, setting up guardrails, and using the Azure Machine Learning Responsible AI Dashboard to assess model fairness and error distributions. - Utilizing tools such as Microsoft GitHub Copilot to accelerate coding, generate documentation, and write unit tests while adhering to enterprise standards

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- Work Independently - Balance, prioritize and organize multiple tasks - Collaborate and communicate effectively with business stakeholders and other team members - Synthesize feedback and adjust plans accordingly - Build strong relationships inside and outside the organization - Develop and write technical documentation - Execute prescribed testing using established procedures and tools - Interpret and analyze test results - Use or maintain testing frameworks, test libraries, databases and test environments - Evaluate AI outputs for bias, hallucinations, and security vulnerabilities, ensuring the system aligns with the Responsible AI Standard. - Effectively explaining complex AI behaviors, limitations, and performance trade-offs to non-technical stakeholders. - Learn to keep pace with the rapid evolution of Microsoft and emerging industry practice

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Required Skills

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Masters in AI or 2 years of AI experience

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Requirement Gathering

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Preferred Skills

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Azure Open AI

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SQL

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C#

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Python