Data & AI Architect

we are seeking a senior Data & AI Architect to design and deliver enterprise data, cloud, AI, and GenAI solutions across a large, complex organization. The role requires strong Azure architecture expertise, multi-cloud experience, hands-on AI/ML and GenAI development, and excellent stakeholder-management skills., * Gather requirements from business and technical stakeholders and convert ambiguous needs into actionable solutions.

• Architect end-to-end data and AI solutions covering ingestion, storage, transformation, modeling, and consumption.
• Design solutions using Azure, AWS, or Google Cloud Platform and modern data/AI technologies.
• Implement GenAI, LLM, RAG, ML pipelines, and agentic/AI-assisted development solutions.
• Develop reference architectures, standards, and governance practices for enterprise data and AI.
• Ensure solutions meet security, privacy, compliance, cost, and data-governance requirements.
• Present architecture and technical recommendations to leadership and governance teams.
• Collaborate with engineering, data science, and product teams to move solutions from concept through production.
• Mentor engineers and analysts on data and AI best practices.

• 8+ years in data engineering, data architecture, software engineering, or related fields.
• 6+ years in an architecture-focused role.
• Hands-on multi-cloud experience across at least two major cloud platforms.
• Strong experience with relational, NoSQL, analytical/warehouse, and vector/graph databases.
• Practical experience with AI/ML, GenAI, LLMs, RAG, and model orchestration.
• Hands-on experience with AI-assisted/agentic development tools.
• Strong requirements gathering, documentation, presentation, and stakeholder-management skills.
• Proven ability to take solutions from concept * approval * production.

Preferred

• Strong recent Azure experience, including Azure Data Services, Synapse/Fabric, Azure OpenAI, or Azure ML.
• Experience with GitHub Copilot, Copilot Studio, or Microsoft 365 Copilot.
• Public-sector, transit, infrastructure, or large-enterprise experience.
• Cloud/data architecture certifications.
• Knowledge of data governance, MLOps, and responsible AI.