**Senior Data Scientist – Generative AI & Conversational Agents - Ventures Team** **About the role** We are looking for a Senior Data Scientist to lead the design, development, and deployment of next-generation AI-powered conversational experiences. This role will drive the technical strategy for GenAI solutions, working closely with Product and Engineering teams to build scalable, production-ready AI applications. **Key Responsibilities** - Design and deploy conversational AI solutions powered by Large Language Models (LLMs). - Build and optimize agent-based workflows, integrating external tools, APIs, and knowledge sources. - Develop prompt engineering strategies and evaluation frameworks to improve model performance. - Architect scalable AI systems, including memory, context management, and retrieval capabilities. - Fine-tune and adapt NLP/transformer models for business-specific use cases. - Partner with cross-functional teams to translate business needs into AI-driven solutions. - Provide technical leadership and mentor team members on AI best practices. **Required Qualifications** - 5+ years of experience in Machine Learning, Data Science, or Artificial Intelligence. - Hands-on experience building and deploying GenAI or Conversational AI applications in production. - Strong experience with LLM platforms such as OpenAI, Claude, Llama, Mistral, or similar. - Experience with agent frameworks such as LangChain, LangGraph, SmolAgents, or equivalent. - Knowledge of RAG architectures, embeddings, vector databases, and context management. - Experience fine-tuning transformer models using frameworks such as Hugging Face. - Strong Python software engineering skills, including Git, testing, CI/CD, and cloud environments. - Excellent communication and stakeholder management skills. **Preferred Qualifications** - Experience with MCP (Model Context Protocol). - Familiarity with observability and evaluation tools such as LangSmith, Phoenix, MLflow, or Weights & Biases. - Experience optimizing LLM applications for scalability, latency, and cost. - Knowledge of AWS, Azure, or Google Cloud. - Experience with Responsible AI and AI Governance.