AI Data Scientist

• Design and deploy next-generation AI solutions leveraging Retrieval-Augmented Generation (RAG), embeddings, vector databases, and agentic architectures for real-world automation.
   

• Build intelligent, agent-based systems for document summarization, knowledge retrieval, content generation, and transforming unstructured data (e.g., PDFs, emails, spreadsheets) into actionable insights.
   

• Implement MCP (Model Context Protocol) and multi-agent frameworks to orchestrate complex reasoning, tool usage, and dynamic workflows across LLMs.
   

• Evaluate, adapt, and fine-tune foundation models (LLMs) for specialized domains, ensuring scalability, reliability, and measurable business impact.
   

• Develop and maintain embedding pipelines and semantic search capabilities, optimizing similarity search in large-scale vector databases.
   

• Work with multi-modal data (text, images, structured/unstructured formats) to deliver rich, context-aware GenAI experiences.
   

• Monitor and enhance model performance focusing on accuracy, latency, and robustness, including LLM evaluation frameworks for continuous improvement. 
   

• Collaborate closely with data scientists to design AI-enhanced analytical workflows, ensuring that GenAI solutions seamlessly integrate with data science models and decision-making pipelines.
   

• Collaborate cross-functionally with engineers, product managers, and business stakeholders to define approaches and deliver production-ready AI systems.
   

• Stay ahead of GenAI and Agentic ecosystem advancements, rapidly prototyping new methodologies and integrating state-of-the-art tools and protocols into real-world applications.
   

What You Bring: