Job Description
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.
