- Strong background in Python, ML engineering and API development (FastAPIs).

- Knowledge of tokenization libraries and GenAI/NLP techniques (RAG, embeddings, transformers).

- Hands-on with GenAI frameworks (LangChain, LlamaIndex, DSPy) and Agentic AI orchestration (LangGraph, MCP, A2A, AutoGen, etc.

- Expertise with vector databases, elastic search, unstructured data.

- Experience with cloud AI/ML services (AWS, Azure, GCP).

Key Responsibilities :

- Design and implement GenAI applications (chatbots, copilots, knowledge assistants).

- Build and manage Agentic AI workflows using orchestration frameworks (LangGraph, Crew AI, MCP, A2A).

- Apply ML/AI techniques (supervised/unsupervised learning, optimization, embeddings, retrieval).

- Integrate AI with enterprise data, APIs, and cloud-native architecture.

- Ensure scalability, security, and cost-effectiveness of deployed solutions.