Senior Azure Cloud & AI Engineer

Senior Azure Cloud & AI Engineer - Master Data Management (Retail) Location: United States (Hybrid / Remote) Experience: 10–15 Years Job Level: Senior / Staff / Principal Individual Contributor Role Summary We are seeking a Senior Azure Cloud & AI Engineer to architect, build, and scale enterprise Master Data Management (MDM) platforms for a large, complex retail environment. This role will lead the design and hands‑on delivery of Location Master and Product Master solutions that serve as foundational systems for Stores, Supply Chain, Merchandising, and Purchasing. The role blends Azure cloud architecture, modern open‑source engineering, data governance, and AI‑driven intelligence, including human‑in‑the‑loop and emerging agentic AI patterns. The architect will also actively leverage AI‑assisted development tools such as GitHub Copilot and Cursor to accelerate delivery while maintaining enterprise standards for security, quality, and maintainability. While the immediate focus is on Location and Product Master, the platform is expected to evolve over time to support additional master data domains. The role is responsible for establishing a flexible, domain‑agnostic MDM foundation that enables future expansion without re‑architecture. Core Master Data Domains Location Master (Initial Focus)

• Enterprise management of:
• Stores
• Terminal Hubs
• Distribution / Ship Centers
• Support for 400+ store attributes, owned by multiple business teams
• Strong requirements for:
• Attribute governance and validation
• Versioning, lineage, and lifecycle management
• Role‑based access and auditability

Product Master (Initial Focus)

• Scalable intake of product data from 800+ vendors
• Normalization and validation of core product attributes
• Enablement for:
• Merchandising review and approval
• Purchase Order eligibility
• Supply chain and store execution

AI‑Driven Product & Data Intelligence

• Design and implement AI‑driven product attribute enrichment
• Apply ML techniques for:
• Attribute inference and classification
• Confidence scoring with explainability
• Data quality and anomaly detection
• Build human‑in‑the‑loop workflows enabling Merchandising teams to:
• Review AI‑generated recommendations
• Approve or override attributes
• Gate products before downstream consumption
• Explore agentic AI patterns, including:
• Data quality monitoring agents
• Vendor data follow‑up agents
• Attribute drift and remediation agents

Master Data Domains – Future Evolution While not required at launch, the MDM platform will be designed to naturally expand over time to support additional retail master data domains, including:

• Vendor / Supplier Master – vendor identity, onboarding, and compliance
• Customer / Party Master – identity resolution and cross‑channel alignment (as applicable)
• Asset & Equipment Master – store and distribution center assets
• Workforce / Employee Master – workforce reference data for store operations

The architect will establish common patterns for identity management, governance, and stewardship that support incremental domain onboarding. Key Responsibilities : Architecture & Technical Leadership

• Architect cloud‑native MDM platforms on Microsoft Azure
• Define target‑state architectures aligned to enterprise, security, and governance standards
• Drive API‑first, domain‑driven, and event‑driven design patterns
• Provide hands‑on technical leadership across engineering, data, and AI teams

Engineering & Platform Delivery

• Design and build services using:
• Spring Boot / Java
• PostgreSQL
• RESTful and asynchronous APIs
• Build intuitive, scalable user experiences using React.js
• Implement CI/CD, observability, reliability, and cost‑optimized cloud patterns

AI‑Assisted Engineering & Developer Productivity

• Build and evolve applications using AI‑assisted development tools, including:
• GitHub Copilot
• Cursor AI or similar AI‑first IDEs
• Apply AI tools for:
• Code generation and refactoring
• API contract creation
• Test automation and documentation acceleration
• Establish guardrails and best practices for AI‑augmented development to ensure:
• Secure, compliant, and maintainable code
• Alignment with enterprise architecture standards

Data, Governance & Integration

• Design flexible data models for high‑attribute retail domains
• Implement stewardship, approval, and audit workflows
• Integrate with enterprise systems using Azure API Management

Cloud & AI Ecosystem

• Leverage Azure services including:
• Azure Kubernetes Service (AKS)
• Azure Functions (as appropriate)
• Azure AI / Azure OpenAI
• Databricks for ML pipelines and enrichment workflows
• Ensure AI solutions meet enterprise standards for:
• Responsible AI usage
• Security and compliance
• Explainability and auditability

Required Qualifications

Experience

• 10–15 years of experience in software engineering, cloud, and data platforms
• Proven experience as a Senior / Principal Cloud or Data Architect
• Demonstrated success delivering enterprise‑scale data or MDM platforms

Technical Skills

• Deep expertise in Microsoft Azure
• Strong hands‑on experience with:
• React.js
• Spring Boot / Java
• PostgreSQL
• Microservices and API‑first architectures
• Practical experience with:
• Databricks
• AI/ML‑driven data enrichment
• Confidence scoring and data quality techniques

AI‑Augmented Development

• Proven experience using GitHub Copilot, Cursor, or similar AI‑assisted development tools in production environments
• Strong judgment in validating and securing AI‑generated code
• Ability to use AI as a force multiplier, not a substitute, for sound engineering practices

Preferred Qualifications

• Retail, merchandising, supply chain, or multi‑vendor product ecosystems
• Experience modernizing or scaling MDM platforms
• Familiarity with agentic AI and AI copilot patterns
• Experience mentoring teams on responsible AI‑assisted development
• Background working in public‑company or regulated environments

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