• Architect a scalable, multi-tenant agentic AI data platform using the Azure technology stack. • Design a hybrid data architecture supporting operational systems, agentic AI workloads, and a knowledge graph • Build infrastructure utilizing vector and graph databases for RAG applications and semantic search • Design and implement comprehensive MLOps platform including deployment management, AI security and safety, and observability on Azure supporting the full ML lifecycle from experimentation to production. • Build automated pipelines using Azure technologies for continuous integration and deployment • Implement real-time inference infrastructure with monitoring, alerting, and automated drift detection • End-to-end lifecycle management including hydration from existing taxonomies/ontologies • Develop high-performance graph query services and APIs for real-time access to supply chain relationships • Deploy automated validation, conflict resolution, and data quality monitoring to ensure graph consistency and accuracy • Implement Infrastructure as Code (IaC) and build CI/CD pipelines for data products and ML models • Set and enforce platform standards for cost control, model/runtime selection, and performance targets (including budgeting, attribution, and optimization for training + inference). • Lead AI governance with Security/Legal/Privacy, turning policy into technical controls (access, auditability, guardrails, retention, and risk management). • Build scalable data + evaluation systems: synthetic dataset generation where appropriate, automated benchmarks, and release quality gates for RAG/agents as well as classical ML. • Create self-service capabilities with comprehensive monitoring and observability • Drive engineering delivery improvements through AI-based code analysis to improve quality, maintainability, and general code health. • Drive engineering efficiency improvements through best practices and adoption of AI-assisted coding tools and capabilities. • Stay on top of new research including cutting edge AI technology. • Democratize AI through TraceGains teams for adoption and deployment across the platform.