Lead Generative AI Engineer

As an AI Solution Designer and Implementor for Retail Analytics Engineering Platforms, your role will involve architecting and implementing enterprise-scale AI/ML solutions. You will be responsible for designing and deploying intelligent AI agents, optimizing NLP/document processing pipelines, and leading the development of Retrieval-Augmented Generation (RAG) systems. Additionally, you will establish LLMOps/MLOps practices and collaborate with cross-functional teams to drive cloud adoption and IT infrastructure modernization. Key Responsibilities: - Architect and implement enterprise-scale AI/ML solutions including Generative AI, Agentic systems, and LLM applications (including fine-tuning). - Design and deploy intelligent AI agents using frameworks like LangChain & LangGraph to enhance user experience and operational efficiency. - Build and optimize NLP/document processing pipelines using GCP/Azure tech stack. - Lead the development of Retrieval-Augmented Generation (RAG) systems and multi-agent architectures. - Establish and maintain robust LLMOps/MLOps practices for model lifecycle management. - Develop and deploy models using PyTorch, MLFlow, and FastAPI. - Ability to implement scalable ML infrastructure, Kubernetes, and CI/CD automation (GitHub Actions). - Collaborate with cross-functional teams to drive cloud adoption and IT infrastructure modernization. Qualifications: - Bachelors degree in Computer Science, Engineering, or related field. - 10+ years of experience in IT systems and AI/ML solution delivery. - Proven track record in designing and deploying enterprise AI solutions. - Strong understanding of cloud-native architectures and scalable AI (Preferred: GCP and/or Azure). Additional Company Details: - Work Location: Bangalore, Chennai, Hyderabad, Pune, Remote - Designation: GEN AI - Work Timings: 2 PM to 11 PM IST Please note that the AI/ML Tools you will be working with include LangChain, LangGraph, PyTorch, and MLFlow. You will also be utilizing Cloud Platforms such as GCP Vertex AI and Kubernetes, along with DevOps & Automation tools like GitHub Actions.,