Senior Data Scientist – Generative AI Applications 

Job Description

We are seeking a Senior Data Scientist (GenAI specialization) who will architect and deploy production-grade GenAI systems that enable natural language querying across our vast document ecosystem.
Primary Responsibilities :

– Build and implement enterprise-level GenAI chatbots capable of natural-language search over extensive document repositories and databases.

– Research and develop multi-agentic systems for production-grade applications that handle large-scale documents and big data

– Optimize vector databases for enterprise-scale semantic search, context management, chat history, and source attribution

– Build document processing pipelines with intelligent chunking, metadata extraction, and multi-format handling

– Implement advanced retrieval strategies: hybrid search, re-ranking, and custom evaluation frameworks

– Work in AWS cloud platform for deployment – handle concurrent requests and scale

– Debug and resolve retrieval quality issues, latency bottlenecks, and cost optimization challenges

– Opportunity to mentor and shape GenAI practices across the organization

– Individual Contributor reporting to Engineering Manager
Skills Required :

– Building GenAI applications from scratch including custom chunking strategies, metadata extraction, multi-format document processing pipelines, indexing, context management, memory management, fine-tuning techniques, model compression techniques, etc. (Must be able to demonstrate through technical justification and code)

– Vector database production implementation: indexing, retrieval optimization, performance tuning

– Embeddings and semantic search: sentence-transformers, similarity search, distance metrics implementation

– Advanced retrieval techniques: hybrid search (semantic + keyword), multi-stage retrieval

– Production LLM integration / hosting: context management, token optimization, streaming responses, citation systems

– Evaluation & metrics for RAG systems & chatbots

– Knowledge of deployment, monitoring, ethics, and governance principles; RESTful API development with FastAPI including error handling
Soft Skills :

– Mentorship abilities : Comfortable teaching GenAI concepts to team members at varying skill levels

– Communication skills : Can explain complex architecture and AI applications behavior to non-technical stakeholders

– Problem-solving mindset : Ability to debug retrieval issues, optimize performance, and handle edge cases

– Self-driven : Can independently research solutions and make architectural decisions

– Collaborative : Works effectively with MLOps, data engineers, and product teams

– Pragmatic approach : Balances innovation with production reliability and business constraints.

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