Procter & Gamble is seeking a Senior Data Architect to join the Supply Chain Innovation organization. This role focuses on leading the design of enterprise-scale Generative AI solutions integrated with P&G;'s data platform. You will own the architecture for how AI systems retrieve, reason over, and act on enterprise data, setting standards for engineering teams.

Key Responsibilities
Own end-to-end architecture for enterprise GenAI solutions, including retrieval, orchestration, integration, and evaluation.
Design production RAG architectures, including document ingestion, chunking, indexing, hybrid retrieval, and relevance tuning.
Architect multi-phase agent and tool-calling workflows with deterministic guardrails.
Design data ingestion and synchronization foundations for AI grounding, including streaming and change data capture.
Enforce data governance, multi-tenant isolation, and Responsible AI principles.
Establish evaluation and observability standards for AI workloads, including automated quality scoring and production tracing.
Manage operational economics, including latency, throughput, and inference costs.

Required Qualifications
Bachelor's degree in Computer Science or related field.




10+ years of experience in software engineering with a focus on architecture and technical leadership of large-scale, high-throughput platforms.
Hands-on experience delivering production Generative AI solutions (RAG, LLM-based classification, agent workflows).
Experience architecting orchestration layers for distributed systems.
Robust background in search and retrieval (vector/semantic similarity, hybrid retrieval).
Experience defining quality and evaluation practices for probabilistic systems.
Proficiency in at least one backend language (Python, Node.js/TypeScript).
Cloud-native engineering experience (Azure) with containerization and CI/CD.

Preferred Qualifications
Knowledge of contemporary lakehouse platforms (Databricks, Delta Lake, Unity Catalog).
Familiarity with AI governance and designing for regulated or highly sensitive data settings.

Generative AIRetrieval-Augmented GenerationLLMAI AgentsPythonNode.jsTypeScriptAzureData ArchitectureDistributed SystemsCI/CDContainerizationData GovernanceDatabricksDelta LakeUnity Catalog

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