Bengaluru, Karnataka
Job Summary
Builds the data and knowledge foundation for grounded, high-quality AI agents. Owns data pipelines, embeddings, vector stores, and RAG components on Google Cloud, extracting and normalizing data from Intel's enterprise sources for AI consumption.
Key Responsibilities
Design and implement data ingestion, transformation, and embedding pipelines.
Extract and normalize data from Databricks, ServiceNow, Snowflake, OneDrive, Adobe, and PDFs.
Build RAG pipelines using Vertex AI Search, BigQuery, AlloyDB, and Vector Search.
Optimize retrieval quality, chunking strategies, and prompt grounding.
Ensure data privacy, PII controls, and access governance; monitor pipeline health and cost.
Skill Requirements
Strong data engineering with GenAI/RAG experience.
Hands-on BigQuery, Vertex AI Search, AlloyDB/Cloud SQL, Dataproc/Dataflow.
Proficient in Python and SQL; embeddings and semantic search.
Experience integrating enterprise data sources (Databricks, ServiceNow, Snowflake).
Other Requirements
Knowledge graphs, data privacy/DLP, IAM.
Adobe systems and unstructured/PDF data extraction.
Pipeline orchestration and observability.
6+ years data engineering with 2+ years GenAI/RAG.
Google Cloud Data Engineer certification preferred.
Offshore (India), aligned to overlap with US stakeholders as needed.
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