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Data IntelligenceRemote, India · Full-time
Data & Knowledge Architect
Build the data, retrieval, knowledge, document, and evaluation foundations that make production AI trustworthy.
INR 12L - 26L
What you'll do
- Design RAG, enterprise search, knowledge graph, and document intelligence architectures
- Define data quality, source mapping, chunking, metadata, permission, and evaluation strategies
- Partner with engineers to implement reliable retrieval and knowledge systems
- Create benchmarks that measure answer quality, source grounding, coverage, and business usefulness
- Advise clients on data modernization required for workflow and revenue intelligence
What we're looking for
Essential
- 4+ years in data architecture, analytics engineering, search, knowledge management, ML/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 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 & perks
Competitive compensation with performance incentives
Remote-first work with flexible collaboration hours
Learning budget for AI, strategy, product, and industry depth
Health coverage and wellness support
Access to current AI tools, research, and cloud sandboxes
Conference attendance and writing/research opportunities
Direct exposure to high-stakes AI transformation work
Clear growth paths across strategy, product, data, and engineering
Join the Data & Knowledge Team
Production AI is only as useful as the context behind it. This team builds the trusted information layer that powers agents, copilots, analytics, and revenue intelligence.
Ready to Build the Knowledge Layer?
Tell us how you design data and retrieval systems people can trust.