Agentic AI Architect

• Experience in Enterprise GenAI and Agentic AI solutions across RAG, AI agents, conversational AI, enterprise search Experience in workflow automation, document intelligence, and AI copilots Experience in planner-executor, reflection, multi-agent, and graph-based orchestration patterns. Experience in Hands-on with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search) Experience in integrating GenAI with AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data platforms.

Preferred Skill and Experience

• Exposure to open-source LLM ecosystems Hugging Face, PyTorch, LoRA, QLoRA, PEFT and models such as Llama, Mistral, Gemma, DeepSeek, and Falcon. Familiarity with multimodal AI, including vision-language models, speech and audio models, and image or video generation. Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins, Terraform, Helm, Kubernetes) and awareness of front-end stacks (React, Angular, TypeScript, GraphQL) used in copilot interfaces.