Data & AI Architect

Job Responsibilities

• Engage with business and operational stakeholders to identify, clarify, and define data and AI use cases.

• Translate ambiguous business needs into clear, actionable requirements and technical specifications.

• Present proposed solutions, technical trade-offs, risks, and business value to stakeholders and governance teams.

• Design end-to-end data and AI solutions covering ingestion, storage, transformation, modeling, serving, and consumption.

• Design and implement solutions using agentic development tools and AI-assisted development workflows.

• Define data and AI reference architectures, standards, patterns, and best practices across multi-cloud and multi-database environments.

• Ensure solutions meet enterprise requirements for security, privacy, data governance, cost efficiency, and regulatory compliance.

• Collaborate with engineering, data science, platform, and product teams to move solutions from design through production.

• Mentor engineers and analysts and provide technical guidance on data and AI best practices.

• Drive solutions from concept and requirements through approval, implementation, and production deployment.

Job Requirements

• 8+ years of experience in data engineering, data architecture, software engineering, or a related technical field.

• 6+ years of experience in an architecture-focused role.

• Hands-on multi-cloud experience with at least two major cloud platforms, such as Azure, AWS, or Google Cloud Platform.

• Strong experience across multiple database technologies, including:

  • Relational databases

  • NoSQL databases

  • Analytical/data warehouse platforms

  • Vector or graph databases

• Practical experience with multiple AI/ML and Generative AI technologies, including LLMs, RAG, ML pipelines, model orchestration, and AI/ML frameworks.

• Hands-on experience with agentic development tooling and AI-assisted development workflows.

• Strong requirements gathering and stakeholder management skills.

• Ability to translate ambiguous business problems into actionable technical requirements.

• Proven experience taking solutions from concept through approval and production implementation.

• Strong understanding of enterprise security, privacy, data governance, and compliance considerations.

Qualifications

• Recent, primarily Microsoft Azure experience, including technologies such as:

  • Azure Data Services

  • Azure Synapse

  • Microsoft Fabric

  • Azure OpenAI

  • Azure Machine Learning

• Hands-on experience with Microsoft Copilot tools, such as GitHub Copilot, Copilot Studio, or Microsoft 365 Copilot.

• Experience working in large, complex enterprise, public-sector, transportation, or infrastructure organizations.

• Relevant cloud, data, or solution architecture certifications preferred.

• Familiarity with enterprise data governance, MLOps, responsible AI, security, and privacy practices.

• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.