Principal GenAI Data Scientist

Principal GenAI Data Scientist

Duration : 3 months Start : ASAP Location : Onsite

Description

We are seeking a highly experienced Principal GenAI Data Scientist to lead the design and development of AI agents, agentic workflows, and production GenAI applications that solve real business problems. You'll be a hands-on technical leader who partners with full-stack engineers, designers, product managers, and data engineers to ship secure, reliable, and scalable GenAI solutions.

Responsibilities

• Architect & build AI agents, agentic workflows, and end-to-end GenAI apps for diverse enterprise use cases.
• Develop, fine-tune, and evaluate LLMs (e.g., Claude / Anthropic, Azure OpenAI, and OSS) and select the right model per use case (cost / latency / quality).
• Design & deploy RAG and Graph-RAG systems using vector stores and knowledge bases; implement semantic chunking, metadata enrichment, and privacy controls.
• Implement embeddings pipelines and integrate with vector stores (e.g., AWS Knowledge Bases / Bedrock, Elastic, MongoDB Atlas).
• Leverage MCP (Model Context Protocol) and A2A (agent-to-agent) patterns to compose multi-agent solutions.
• Build notebooks & services in Python / Jupyter; use SageMaker and MLFlow / Kubeflow on EKS for training, tracking, and deployment.
• Curate enterprise data via connectors; orchestrate multimodal ETL / ELT (PDF / audio / video) with Spark / PySpark.
• Integrate GenAI capabilities into enterprise platforms via APIs and standardized GenAI patterns.
• Establish evaluation & safety : define automatic evals, bias testing, guardrails, and deployment readiness criteria.
• Collaborate cross-functionally with UI / microservices teams to deliver polished, production solutions and measurable business value.
• Document & mentor : codify patterns, playbooks, and best practices for repeatable delivery.

Must-Have Qualifications

Required Experience

Preferred Qualifications

Nice to Have (Role-Aligned Extras)