HCLTech—Technical Lead

Job description

Description: 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.