• Implement DLP, MIP, retention, Sensitivity Labels, and secure configuration. • Administer and operationalize enterprise LLM platforms (Copilot, Gemini, ChatGPT Enterprise, Claude). • Develop connectors, automations, and reusable patterns for AI and M365 workloads. • Troubleshoot permission issues, data routing, and cross workspace access. • Provide hands on engineering for data governance enforcement.

• Współtworzenie frameworków ewaluacyjnych, rozwiązań w obszarze proctoringu oraz krytycznych mechanizmów bezpieczeństwa. • Ocena i wdrażanie najnowocześniejszych (state-of-the-art) technik AI/ML. • Implementacja systemów automatycznego generowania treści oraz integracja rozwiązań AI (LLM, OCR) z workflowami i narzędziami automatyzacji. • Tworzenie eksperymentów mających na celu walidację wydajności modeli oraz ich realnego wpływu na biznes oraz optymalizacji kosztów i opóźnień (latency). • Projektowanie, budowanie i wdrażanie skalowalnych usług oraz pipelines AI. • Udział w regularnych konsultacjach technicznych oraz ścisła współpraca z CTO. • Rozwijanie nowoczesnego środowiska programistycznego wspieranego przez AI, aktywne eksperymentowanie i śledzenie najnowszych technologii (LLM, agenci).... • Współpraca z działami Produktu i Designu w celu definiowania funkcji napędzanych przez AI. • Produkcyjne wdrażanie modeli z wykorzystaniem nowoczesnych praktyk MLOps oraz LLMOps oraz budowa systemów monitoringu i zabezpieczeń (guardrails).

• Build and maintain AI-powered data pipelines and extraction processes (batch and streaming) from internal relational data sources and unstructured documents (PDF, Word, PowerPoint) into structured datasets within Databricks. • Design and manage text embeddings and vector stores within Databricks for use with vector indexing and retrieval solutions. • Design, develop, and maintain custom tools implemented as MCP servers and Databricks applications to extend agent and model capabilities. • Design, develop and implement AI Agents using frameworks like LangChain and LangGraph. • Implement LLM scorers to validate and monitor agents, applications and models. • Prevent issues like hallucinations or unnecessary actions through structured testing and guardrails. • Drive continuous improvement through prompt engineering, pipeline optimization, vector store tuning, and scorer refinement to ensure high-quality LLM responses. • Collaborate on production deployments, monitoring, and scalability of ML and LLM-based services.

The Artificial Intelligence (AI) Solutions Architect (Contractor) will work with our existing internal AI product management team, Vendor Teams and existing development staff to develop, enhance and streamline our AI systems. Lead the design and implementation of secure, scalable AI and Agentic AI solutions aligned with DES mission, policies, and public-sector standards. Define end-to-end AI architectures including data ingestion, RAG pipelines, LLM orchestration, and human-in-the-loop workflows. Provide technical leadership, relevant architectural documentation for approvals, and guidance to internal teams and system integrators. Ensure compliance with State of Arizona security, privacy, accessibility, and data-governance requirements (PII, HIPAA, CJIS where applicable). Establish reference architectures and best practices for responsible, ethical, and compliant AI use across DES. Evaluate and integrate AI platforms, cloud services, and vendor solutions in coordination with procurement and legal teams. Design architectures that support explainability, auditability, bias mitigation, and transparency in decision-support systems. Collaborate with DevOps (cloud ops), cybersecurity, and data teams to operationalize AI solutions from proof of concept to production systems. Support AI strategy, roadmap development, and executive briefings to scale AI capabilities across DES programs.