Role : Lead Engineer Generative AI & Agentic Systems

Location : Bangalore (Hybrid)

Total Experience : 7-12 Years

Notice Period : 0-30 days

Job Summary :

We are seeking an experienced Lead Engineer Generative AI & Agentic Systems to design, develop, and deploy production-grade generative AI solutions and intelligent agentic applications. As part of EXLs Digital AI R&D Innovation team, you will lead initiatives leveraging frameworks such as LangGraph, AutoGen, and LangChain to build multi-agent workflows, orchestrate intelligent systems, and deliver scalable APIs.

Key Responsibilities :

- 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.

Required Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, Data Engineering, AI/ML, or related field.

- 7+ years of total professional experience in AI/ML, Data Science, or related fields.

- 5+ years of hands-on experience in Python with strong software engineering practices.

- At least 3 years of experience in AI/ML engineering, including 2+ years of hands-on experience in Generative AI / Agentic AI.

- Hands-on experience with deep learning frameworks (PyTorch, TensorFlow).

- Expertise in large language models (LLMs), prompt engineering, and fine-tuning.

- Proven track record of deploying at least 3 GenAI/Agentic AI projects into production.

Preferred Qualifications :

- 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).

- Contributions to open-source AI/ML projects or published research in generative AI.