AI & Data Architect / SME

Looking for a senior AI & Data SME with deep expertise in enterprise data engineering, GenAI, RAG, and Google Cloud data services to support an enterprise Agent factory/AI platform., * Define the enterprise data-to-AI strategy for ingestion, normalization, embeddings, vector stores, and RAG grounding.

• Architect and oversee data pipelines from enterprise source systems into Google Cloud.
• Own retrieval quality, including chunking strategies, embedding models, hybrid search, and grounding accuracy.
• Establish and enforce AI data governance, privacy, security, lineage, and data quality standards.
• Guide model selection and cost/performance optimization for data-intensive AI agent workloads.
• Partner with architects, developers, and engineering teams on data readiness and AI knowledge design.
• Serve as a senior technical authority in stakeholder discussions around AI, data architecture, and platform dependencies.
• Mentor Data & AI Engineers and establish standards for reusable data assets and AI-ready knowledge.

Good to Have:

• Knowledge Graphs

  GraphRAG

  Corrective RAG / Self-RAG

• Snowflake / Databricks Certifications
• Google Professional Data Engineer certification
• AI evaluation frameworks and observability

• 9-12+ years in Data engineering/data architecture with recent GenAI/RAG delivery

• Strong Enterprise Data Engineering

  ETL/ELT

  Data Modeling

  Data Quality

• Hands-on experience with Google Cloud Data Stack

• BigQuery

  Vertex AI Search

  AlloyDB / Cloud SQL

  Dataflow

  Dataproc

• Strong expertise in RAG Architecture

  Embeddings

  Vector Databases

  Chunking

  Hybrid/Semantic Search

• Experience with RAG Grounding & Retrieval Quality Evaluation

• Enterprise data integration experience with Databricks

  ServiceNow

  Snowflake

  SharePoint / OneDrive

  Adobe

  PDFs

• Strong Python & SQL skills with solid understanding of GenAI / LLM data patterns

• Experience with AI Data Governance

  PII

  DLP

  Data Privacy

  Data Lineage

  Access Management

• Ability to architect data pipelines from enterprise sources into Google Cloud
• Strong understanding of AI data readiness, knowledge design, and grounded AI responses
• Experience advising architects and developers on data architecture and AI/ML workloads
• Strong communication skills with experience engaging senior technical stakeholders, A senior AI & Data Architect / SME who can bridge enterprise data engineering and GenAI, with hands-on expertise in Google Cloud, RAG, data pipelines, governance, and AI-ready data architecture.