Director Of Data And Ai

15 hours ago


Ahmedabad, India Whatjobs IN C2 Full time

About the Company JOB DESCRIPTION As the Director of Data & AI Engineering, you will lead the foundation of our Intelligence Stack — driving metadata management, data cataloging, and next-generation data pipelines that fuel our multi-agent AI platforms and Trust Layer architecture. About the Role As the Director of Data & AI Engineering, you will lead the foundation of our Intelligence Stack — driving metadata management, data cataloging, and next-generation data pipelines that fuel our multi-agent AI platforms and Trust Layer architecture. Responsibilities Own the Data Foundation: Lead initiatives around metadata management, data cataloging, lineage, and governance to make data discoverable, trustworthy, and reusable across AI systems. Architect Scalable Data & AI Infrastructure: Design unified data and model pipelines integrating ingestion, transformation, RAG, and inference layers. Lead High-Performing Teams: Build and mentor cross-functional teams across data engineering, AI engineering, and MLOps, setting standards for performance, observability, and automation. Operationalize AI with Data: Develop data services and vectorized pipelines that continuously enrich AI reasoning, retrieval, and contextual grounding. Integrate Across Ecosystem: Collaborate with Product, Infra, and Cloud teams to embed AI and data layers into enterprise applications, analytics, and automation workflows. Govern with Trust: Define and implement guardrails for data quality, lineage, bias detection, and model compliance — aligning to our AI safety and trust principles. Shape Data & AI Strategy: Evolve ProductSquads’ enterprise data fabric to power multi-tenant AI agents and real-time decision systems. Qualifications Experience building centralized metadata and data catalog systems (e.G., Amundsen, DataHub, Open Metadata). Hands-on expertise with vector databases (Pinecone, Milvus, FAISS) and contextual retrieval architectures. Understanding of knowledge graphs, semantic search, and data lineage frameworks. Proven record of embedding AI + data systems into enterprise-scale applications. Passion for leading data-driven innovation and mentoring teams that bridge data engineering with applied AI. Required Skills Experience building centralized metadata and data catalog systems (e.G., Amundsen, DataHub, Open Metadata). Hands-on expertise with vector databases (Pinecone, Milvus, FAISS) and contextual retrieval architectures. Understanding of knowledge graphs, semantic search, and data lineage frameworks. Proven record of embedding AI + data systems into enterprise-scale applications. Passion for leading data-driven innovation and mentoring teams that bridge data engineering with applied AI. Preferred Skills Experience building centralized metadata and data catalog systems (e.G., Amundsen, DataHub, Open Metadata). Hands-on expertise with vector databases (Pinecone, Milvus, FAISS) and contextual retrieval architectures. Understanding of knowledge graphs, semantic search, and data lineage frameworks. Proven record of embedding AI + data systems into enterprise-scale applications. Passion for leading data-driven innovation and mentoring teams that bridge data engineering with applied AI.



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