Technology Architect - Artificial Intelligence and Generative AI

Technology Architect - AI/GenAI-Q2 FY 27 • • • Design and develop enterprise-grade Generative AI solutions using Python and modern AI frameworks. • Build AI applications using LLMs, embeddings, prompts, function calling, tool usage, and agentic AI patterns. • Implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval and generation use cases. • Design end-to-end AI solutions covering: o Data ingestion o Data processing o Retrieval o Generation o Evaluation • Work with Agentic AI frameworks such as CrewAI, LangChain, LangGraph, LlamaIndex, AutoGen, and Langfuse. • Apply prompt engineering strategies to improve LLM accuracy, reliability, and usability. • Evaluate the suitability of fine-tuning vs RAG based on business and technical requirements. • Support LLM fine-tuning workflows including instruction tuning and supervised fine-tuning. • Manage data preparation for fine-tuning, including train/validation splits, data quality checks, and contamination prevention. • Deploy AI workloads on cloud platforms such as Azure, AWS, or GCP. • Containerize AI applications using Docker and work with basic Kubernetes concepts. • Apply model engineering best practices for scalable, reliable, and production-ready AI systems.