Lead the development of cutting-edge Generative AI applications, building robust solutions from the ground up. This role involves architecting and implementing complex AI systems, fine-tuning advanced models, and ensuring seamless integration across various platforms.

As a Generative AI Senior Lead, you will be instrumental in driving innovation and delivering high-impact solutions. Your expertise will guide the team in leveraging the latest AI frameworks and technologies to solve challenging business problems and advance our AI capabilities.

Develop and deploy generative AI applications using leading frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. Craft efficient and maintainable Python code for sophisticated AI solutions. Design scalable architectures for managing large volumes of structured and unstructured data. Implement multi-modal LLM applications, including text, vision, and speech models. Fine-tune small language models for specific industry needs and use cases. Integrate front-end interfaces using React, Streamlit, and AG Grid. Develop data modernization and transformation pipelines to support AI initiatives. Build OCR and document intelligence solutions. Utilize cloud platforms such as Azure, GCP, and AWS for application deployment and management. Apply advanced fine-tuning techniques like PEFT, QLoRA, and LoRA. Implement LLMOps for streamlined CI/CD and monitoring. Ensure responsible AI practices are followed throughout the development lifecycle. Implement RAG and Modular RAG architectures for improved model performance. Automate data curation and preprocessing pipelines. Create comprehensive technical documentation. Collaborate effectively with cross-functional teams, including data scientists, engineers, and product managers. Mentor junior developers to foster technical growth and a culture of innovation.

A minimum of 8 years of experience in application development and AI. Proficiency in Python programming for AI solutions and experience with frameworks such as Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. Demonstrated ability in designing large-scale data architectures and handling multi-modal LLM applications. Experience with front-end integration using React, Streamlit, and AG Grid. Skilled in cloud platforms (Azure, GCP, AWS) and fine-tuning LLMs using techniques like PEFT, QLoRA, and LoRA. Familiarity with LLMOps, RAG, and Responsible AI practices is essential. Strong understanding of API integration (REST, SOAP) and OCR technologies. Excellent collaboration and mentorship capabilities are required.