Artificial Intelligence Architect with Azure

IT Engagements is a global staff augmentation firm providing talent on-demand and total workforce solutions. This role is with one of our premium clients.

About the role

Location: New York City, NY (Hybrid). Relocation assistance available for nearby states only. Duration: 24 months. Visa sponsorship: H1B, H4EAD, or US Citizenship recommended; GCEAD or Green Card considered secondarily. Candidates must have recent project experience in one U.S. state.

Requirements

• 15+ years of overall experience in data engineering, data architecture, software engineering, or a closely related field, with 6+ years in an architecture-focused role.
• Multi-cloud experience: hands-on design and delivery across at least two major cloud providers (e.g., Azure, AWS, GCP).
• Multi-database experience across relational, NoSQL, analytical/warehouse, and vector or graph database technologies.
• Multi-AI experience: practical work across a range of AI/ML and generative-AI frameworks, models, and platforms (e.g., LLMs, ML pipelines, RAG, model orchestration).
• Strong requirements-gathering and stakeholder-facing skills: proven ability to extract clarity from ambiguity and write actionable specifications.
• Excellent written and verbal communication; able to explain complex technical concepts to non-technical audiences and secure buy-in.
• Hands-on experience delivering solutions with agentic development tooling / AI-assisted development workflows.
• Demonstrated experience taking solutions from concept through approval to production implementation.

Skills

• Primary recent experience on the Microsoft Azure stack (e.g., Azure Data services, Synapse/Fabric, Azure OpenAI, Azure ML).
• Hands-on development experience with Microsoft Copilot tooling (e.g., GitHub Copilot, Copilot Studio, M365 Copilot). Exceptional candidates without Copilot experience will be considered.
• Experience in large, complex, or public-sector / transit / infrastructure organizations.
• Relevant cloud or data architecture certifications.
• Familiarity with enterprise data governance, MLOps, and responsible-AI practices.