Data Scientist
EXL · Gurugram
- Lead the design and implementation of agentic AI workflows using LangGraph, AutoGen, LangChain, or similar frameworks.
- Architect and optimize scalable APIs (REST/WebSocket) for production deployment.
- Develop, fine-tune, and integrate large language models into enterprise applications.
- Deploy and maintain at least 3 GenAI/Agentic AI projects in production, ensuring reliability, scalability, and performance.
- Integrate SQL, No-SQL, and vector databases such as Postgres, MongoDB, and ChromaDB.
- Implement graph databases (Neo4j) for knowledge graph-based use cases.
- Provide technical leadership and mentorship to engineering teams.
- Collaborate with cross-functional stakeholders to identify and deliver GenAI solutions across multiple business domains.
- Ensure robustness, security, and compliance of deployed AI systems.
- Stay current with trends in GenAI, deep learning, and orchestration frameworks.
- Document and present technical solutions to both technical and non-technical audiences.
- Familiarity with LangGraph, AutoGen, LangChain, or similar agentic AI frameworks.
- Experience with multi-agent systems and orchestration of intelligent workflows.
- Knowledge of MLOps practices (CI/CD, model monitoring, retraining pipelines).
- Strong problem-solving skills and ability to thrive in fast-paced R&D environments.
- Contributions to open-source AI/ML projects or published research in generative AI.