Senior GenAI SME :9+ years of experience : Skill : Proven Experience: Demonstrated track record of architecting and building generative AI applications in a professional environment.AWS Expertise: Deep, hands-on experience with the AWS cloud platform, especially Amazon Bedrock, Lambda, S3, and other services relevant to AI/ML workloads. Foundational Model Proficiency: Extensive experience working with large language models (LLMs) and multi-modal models, specifically with Anthropic's Claude via API and models within Bedrock. RAG Mastery: In-depth, practical knowledge of building and refining RAG systems, including vector databases (e.g., Pinecone, Chroma), embedding models, and retrieval strategies. Agentic AI Frameworks: Hands-on experience with agent-based frameworks, with a strong preference for CrewAI. Strong Coding Skills: High proficiency in Python and relevant AI/ML libraries (e.g., LangChain, Boto3, Transformers, PyTorch/TensorFlow). Speed & Reliability: Ability to work autonomously and deliver high-quality, robust solutions with speed and precision. Responsibilities : : Architect & Develop: Lead the design and implementation of scalable, high-performance generative AI solutions on the AWS platform. Rapid Prototyping & Coding: Write production-quality code to quickly build and iterate on proofs-of-concept and full-scale applications. RAG Implementation: Engineer and optimize sophisticated Retrieval-Augmented Generation (RAG) pipelines to ground models in proprietary data, ensuring factual accuracy and relevance. Agentic AI Systems: Design and build multi-agent AI systems using frameworks like CrewAI to automate complex workflows and tackle dynamic tasks. Model Strategy: Provide expert guidance on the selection, fine-tuning, and application of foundational models available through Amazon Bedrock and direct API access (e.g., Claude). Technical Leadership: Mentor team members, establish best practices for GenAI development, and stay at the forefront of the latest advancements in the field. RTH - Y - U2XM9X