VP, AI Data Architect (L12)
INR 3000K-4000K (estimate) Senior-level Full Time
Tasks
- Build data preparation and curation pipelines for fine tuning
- Create AI ready data strategy and roadmap
- Define data and AI foundations architecture
- Define data contracts SLAs and integration patterns
- Design canonical data models and semantic layers
- Develop batch and streaming data pipelines for RAG systems
- Drive metadata and catalog tool adoption
- Enforce AI data governance policies
- Establish data quality and observability for AI data
- Expose data services as platform primitives for agent builders
- Implement RAG evaluation strategies
- Integrate external data into AI workflows and monitoring
- Lead RAG data infrastructure design and governance
- Optimize RAG retrieval chunking embeddings indexing and ranking
- Own data sourcing modeling governance delivery for RAG
- Partner on model risk and privacy compliance for AI use
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS Glue | AWS Glue Data Catalog | AWS IAM | AWS Lake Formation | Amazon Redshift | Amazon S3 | Apache Iceberg | B testing | CDC | CI/CD | Chunking | Data Architecture | Data Catalog | Data Governance | Data Modeling | Data Observability | Data Quality | Drift Detection | ELT | ETL | Embeddings | Entity Resolution | Feature Stores | Fine Tuning | Glue Data Catalog | Google BigQuery | Hybrid search | IAM Identity Center | Identity Center | Indexing | Infrastructure as Code | Knowledge graphs | Lake Formation | Machine Learning | Machine Learning Pipelines | Metadata Management | Model Fine-tuning | Object storage | OpenSearch | PGVector | Pinecone | PostgreSQL | Python | RAG | Ranking | Re-ranking | Retrieval-Augmented Generation | Semantic Search | Semantic layer | Snowflake | Streaming Data | Vector Databases | Vector Search | “as-code”
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