Technical Project Lead/Architect/GenAI Lead AWS Cloud & GenAI

As a highly skilled and visionary Technical Lead with 6-8 years of working experience on AWS & GenAI, you will be spearheading next-generation AI initiatives. Your role will involve deep expertise in Large Language Models (LLMs) integration, cloud-native architecture, and hands-on leadership in delivering scalable GenAI solutions on cloud platforms. You will lead multiple GenAI projects, driving innovation from concept through deployment, ensuring robust, scalable, and efficient AI-powered applications. **Key Responsibilities:** - Lead the design, development, and deployment of GenAI projects leveraging Large Language Models (LLMs) on cloud platforms, primarily AWS. - Architect and implement scalable, event-driven cloud-native solutions using AWS Lambda, SNS/SQS, Step Functions, and related services. - Drive prompt engineering strategies including prompt versioning, optimization, and chain-of-thought design to enhance model performance. - Oversee fine-tuning, embeddings, and conversational flow development to build intelligent, context-aware AI applications. - Integrate and manage LLM APIs such as Azure OpenAI and other emerging models to deliver cutting-edge AI capabilities. - Utilize vector databases (ElasticSearch, Open Search, or similar) for embedding-based search and Retrieval-Augmented Generation (RAG). - Lead model evaluation efforts including output analysis, performance tuning, and quality benchmarking to ensure high standards. - Collaborate with cross-functional teams including data scientists, engineers, and product managers to align AI solutions with business goals. - Mentor and guide technical teams on best practices in GenAI development and cloud architecture. - Stay abreast of the latest advancements in AI, cloud technologies, and LLM frameworks to continuously innovate and improve solutions. **Skills & Experience:** - Proven hands-on experience integrating Large Language Models (LLMs) into real-world applications. - Strong programming skills in Python and experience with web frameworks such as FastAPI or Flask. - Expertise in cloud architecture, particularly AWS services including Lambda, SNS/SQS, Step Functions, and event-driven design patterns. - Deep knowledge of LLM APIs, with mandatory experience in Azure OpenAI; familiarity with other models like LLaMA is a plus. - Experience working with vector databases such as ElasticSearch, Open Search, or other vector search engines. - Proficiency in prompt engineering techniques including prompt versioning, optimization, and chain-of-thought design. - Familiarity with LLM frameworks such as LangChain and LlamaIndex. - Experience with embedding-based search and Retrieval-Augmented Generation (RAG) methodologies. - Strong skills in model evaluation, including output analysis, performance tuning, and quality benchmarking. - Excellent leadership, communication, and project management skills.,