data scientist architect

Role & responsibilities

We are looking for an experienced Data Science Architect with a strong background in Data Science, Machine Learning, and Generative AI. The candidate should have hands-on experience designing and implementing RAG-based solutions using LangChain and integrating Large Language Models (LLMs) into enterprise applications.

Key Responsibilities

• Architect and develop enterprise-grade GenAI and RAG solutions.
• Build RAG pipelines covering document ingestion, chunking, embeddings, retrieval, prompt orchestration, and response generation.
• Develop LLM applications using LangChain.
• Work with vector databases and semantic search technologies.
• Evaluate and optimize retrieval quality, LLM responses, latency, and overall solution performance.
• Design traditional Data Science/ML solutions using Python and relevant ML frameworks.
• Define scalable AI/ML solution architectures and integration patterns.
• Work closely with data engineering, application development, cloud, security, and business teams.
• Provide technical guidance on AI architecture, solution design, and implementation.

Mandatory Skills

• RAG (Retrieval-Augmented Generation)
• LangChain
• Generative AI / LLMs
• Python
• Machine Learning / Data Science
• NLP and embeddings
• Vector databases / vector search
• Prompt engineering
• LLM application development
• API/application integration
• Strong solution architecture and design experience

Preferred Skills

• LangGraph
• Azure OpenAI / OpenAI or equivalent LLM platforms
• Azure AI Search or similar retrieval/search platforms
• Databricks / Spark
• MLflow / MLOps
• FAISS, Pinecone, Weaviate, Chroma or equivalent vector stores
• Cloud experience, preferably Azure

Preferred candidate profile