Data Scientist Specialist

We are looking for a Principal Gen AI Scientist with deep expertise in Generative AI to lead the design and development of AI Agents, Agentic Workflows, and Gen AI applications for complex business challenges.

This role requires advanced proficiency in LLMs, RAG architectures, multi-modal AI, and AWS-based deployments.

• Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications.
• Develop and fine‑tune lightweight LLMs; evaluate models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives.
• Design and deploy Retrieval‑Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.
• Curate enterprise data and integrate with AWS Bedrock Knowledge Base/Elastic.
• Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication.
• Build and maintain Jupyter‑based notebooks using Sage Maker and MLFlow/Kubeflow on Kubernetes (EKS).
• Collaborate with cross‑functional teams to deliver full‑stack Gen AI experiences.
• Integrate GenAI solutions with enterprise platforms via APIs and standardized patterns.
• Establish validation procedures with Evaluation Frameworks, bias mitigation, and safety protocols.
• Design and build robust ingestion pipelines for unstructured data (PDFs, video, audio) using semantic chunking and privacy controls.
• Orchestrate multimodal pipelines using scalable frameworks (Apache Spark, PySpark).
• Implement embeddings and integrate with vector stores for RAG architectures.

• MS/PhD in AI/Data Science.
• 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions.
• Expertise in prompt engineering, fine‑tuning, RAG, Graph
  
  RAG, and vector databases.
• Proven experience with AWS Sage Maker, Bedrock, MLFlow on EKS.
• Strong programming skills in Python and ML libraries (Transformers, Lang Chain).
• Deep understanding of Gen AI system patterns, architectural best practices, and evaluation frameworks.
• Ability to work in cross‑functional agile teams.
• Github Code Repository link required for each candidate.

• Published contributions or patents in AI/ML/LLM domains.
• Hands‑on experience with enterprise AI governance and ethical deployment frameworks.
• Familiarity with CI/CD practices for ML Ops and scalable inference APIs.
• Experience building AI agents and deploying Gen AI applications to production.