Duties & Responsibilities :

- Translate business requirements into scalable and well-documented ML pipelines and AI solutions using Databricks, Azure AI, and Snowflake.

- Architect and implement scalable GenAI solutions using Azure/ GCP AI, Databricks, and Snowflake

- Develop and deploy agentic workflows using LangChain, LangGraph, and OpenAI Agents SDK for autonomous task execution.

- Lead experimentation and fine-tuning of LLMs (e.g., GPT-4, Claude, LLaMA 2) for enterprise use cases such as summarization, personalization, and content generation.

- Integrate GenAI models into business applications with Human-in-the-Loop (HITL) validation and feedback loops.

- Build and maintain MLOps/LLMOps pipelines using MLflow, ONNX, and Unity Catalog for reproducibility and governance.

- Monitor model performance and ensure responsible AI operations through observability tools like OpenTelemetry and Databricks AI Gateway.

- Stay current with GenAI and LLM advancements, including frameworks like LangChain, LlamaIndex, and Gemini, and apply them to enterprise use cases.

- 5-8 years of experience in AI/ML engineering, with at least 2 years focused on GenAI and LLMs.

- Proven experience deploying agentic AI systems in production environments.

- Strong understanding of NLP, deep learning, and multi-modal AI (text, image, audio).

- Experience with enterprise-grade AI governance and security practices.