Data Scientist

About the Role

Key Responsibilities

• Design and develop production-grade GenAI applications and AI Agents. Build Enterprise Copilots using LLMs/SLMs, MCP, RAG, and Graph RAG. Develop Knowledge Management solutions leveraging Knowledge Graphs, vector databases, and enterprise data. Train, fine-tune, optimize, and evaluate LLMs/SLMs for domain-specific use cases. Build scalable Python-based AI services and APIs. Deliver enterprise AI solutions using AWS Bedrock and/or Google Vertex AI. Collaborate with architects, data engineers, and business stakeholders to deliver AI-driven business outcomes.

Required Skills

• Strong foundation in Statistics, Machine Learning, Deep Learning, NLP, and Generative AI. Expert Python programming with experience building production-grade AI/GenAI applications. Hands-on experience with AI Agents, Multi-Agent Systems, Enterprise Copilots, RAG, Graph RAG, embeddings, vector databases, and agent orchestration frameworks. Strong understanding of Knowledge Management, Knowledge Graphs, Semantic Search, and enterprise retrieval architectures. Experience developing MCP (Model Context Protocol)-based applications. Experience training, fine-tuning, and optimizing LLMs/SLMs. Expertise in AWS Bedrock and/or Google Vertex AI, including AgentCore/Agents, Knowledge Bases, Guardrails, Prompt Management, Model Customization, Vertex AI Agent Builder, and enterprise AI deployment. Experience with cloud-native development, APIs, containers, Kubernetes, and MLOps.