Join our innovative team as a Generative AI Lead and spearhead the development of cutting-edge AI applications. This role is pivotal in designing, building, and deploying sophisticated GenAI solutions that leverage the latest advancements in AI technology. You will be instrumental in shaping the future of AI development within our organization.

This position offers an exciting opportunity to work with a dynamic team and contribute to high-impact projects. We are looking for a visionary leader to drive our Generative AI initiatives forward and mentor emerging talent.

Lead the end-to-end development of Generative AI applications using frameworks such as Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. Develop robust and efficient Python code for complex AI solutions. Design and implement architectures capable of handling massive structured and unstructured datasets. Work with multi-modal LLMs, including text, vision, and speech models, and fine-tune Small Language Models for specific domains. Integrate user interfaces using React, Streamlit, and AG Grid, ensuring seamless connections with GenAI backends. Build data modernization and transformation pipelines, and develop OCR and document intelligence solutions. Utilize cloud platforms like Azure, GCP, and AWS for deployment and management, and implement advanced fine-tuning techniques. Establish and manage LLMOps pipelines, ensuring ethical AI practices and implementing RAG architectures. Automate data curation processes, create comprehensive technical documentation, and collaborate with cross-functional teams. Mentor junior developers to foster a culture of excellence and innovation.

A minimum of 6 years of professional experience is required for this role. Expertise in building GenAI applications using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. Strong proficiency in Python programming for AI development. Experience in designing large-scale data handling architectures for structured and unstructured data. Familiarity with multi-modal LLMs (text, vision, speech) and fine-tuning SLMs. Proficiency in front-end technologies such as React, Streamlit, and AG Grid. Knowledge of data modernization, transformation, OCR, and document intelligence solutions. Experience with API integration using REST, SOAP, and cloud platforms (Azure, GCP, AWS). Expertise in LLM fine-tuning (PEFT, QLoRA, LoRA) and LLMOps. Understanding of Responsible AI practices, RAG, and Modular RAG. Ability to automate data curation and create technical documentation. Excellent collaboration and mentorship skills are essential.