Data & Knowledge Architect

Role overview Architect the data and knowledge foundations that help production AI systems retrieve useful information and provide trustworthy answers. You’ll shape retrieval, search, document, and evaluation systems, working with engineers and advising on the data improvements needed to support AI-enabled workflows and analytics.

Responsibilities - Design architectures for retrieval-augmented generation (RAG), enterprise search, knowledge graphs, and document intelligence. - Define approaches to data quality, source mapping, chunking, metadata, permissions, and evaluation. - Partner with engineers to implement reliable retrieval and knowledge systems. - Build benchmarks for answer quality, source grounding, coverage, and business usefulness. - Advise on data modernization for workflow and revenue intelligence.

Requirements - At least four years of experience in data architecture, analytics engineering, search, knowledge management, ML or AI engineering, or business data platforms. - Experience with SQL, data modeling, APIs, vector databases, document processing, or BI systems. - Understanding of RAG, embeddings, metadata, permissions, retrieval evaluation, and source grounding. - Strong architecture documentation and communication skills.

Nice to have - Experience with tools such as Pinecone, Weaviate, Qdrant, pgvector, Elasticsearch, Snowflake, BigQuery, dbt, or Airflow. - Experience with regulated or permission-sensitive knowledge systems. - Background in analytics, data governance, or enterprise search.

Benefits and work setup - Full-time, remote role based in India. - Work with business, design, data, and engineering teams to build information systems for agents, copilots, analytics, and revenue intelligence.