Lead cutting-edge AI innovation as an AI Decision Science Manager, focusing on the design, development, and deployment of advanced AI agents and multi-modal AI solutions. You will drive the autonomous execution of complex business workflows, shaping client strategies in Generative AI and agentic AI. Your role involves defining and implementing Gen AI strategies to deliver large-scale AI initiatives, fostering innovation, cultivating client relationships, and charting the course for autonomous, AI-driven business transformation.

- Provide strategic leadership and oversee the complete lifecycle of AI projects, from initial requirements and architecture to deployment and ongoing support. - Offer expert guidance on advanced Generative AI and Agentic AI technologies to cross-functional teams. - Define and articulate a clear strategic vision for AI agent solutions, ensuring they align with client business goals. - Act as a trusted advisor to clients, translating intricate AI concepts into practical business solutions. - Lead discussions on best practices, risk management, AI safety, and governance for Generative AI. - Design and implement sophisticated AI agents using frameworks like AI Refinery, LangChain, AutoGen, CrewAI, and custom architectures. - Develop multi-agent systems capable of collaborative decision-making and autonomous complex workflow execution. - Integrate Model Context Protocol (MCP) for seamless communication between AI systems and external tools/APIs. - Build and deploy Generative AI applications with advanced reasoning, planning, and execution capabilities. - Develop solutions leveraging Computer Vision, Machine Learning, and Large Language Models (LLMs). - Define data requirements, perform data cleaning, aggregation, analysis, and quality assessments. - Build, deploy, train, and fine-tune AI models and Generative AI applications, including LLMs. - Evaluate model performance and drive iterative improvements. - Collaborate on integrating AI solutions into end-to-end workflows for scalability. - Utilize cloud platforms such as AWS, Azure, or GCP for model development and deployment. - Stay abreast of AI and Data Science advancements, exploring innovative techniques and frameworks. - Document methodologies and findings to facilitate effective knowledge sharing.

- Minimum 7 years of experience in AI/ML, with a proven track record of leading teams in Generative AI application and agentic system delivery, ideally in a consulting or client-facing capacity. - Deep expertise in agentic AI systems and a demonstrated history of building autonomous AI solutions capable of executing complex business workflows. - Strong understanding of AI safety, alignment, and governance principles for autonomous systems. - Experience with enterprise-grade AI agent deployments and production system management. - Expert proficiency in Generative AI, Agentic AI Systems, Model Context Protocol (MCP), LLMs, Multi-Agent Systems, Python, SQL, and AI Agent Orchestration frameworks. - Familiarity with cloud platforms (AWS, Azure, GCP), Docker, Kubernetes, Spark, and MLOps pipelines for agentic systems. - Specialized knowledge in NLP, Computer Vision, Reinforcement Learning for agent training, and Multi-modal AI systems. - Experience in developing and deploying AI/ML models. - Bachelor's or Master's degree (BE/BTech/MBA/MS) in Statistics, Computer Science, Mathematics, AI/ML, or related fields with an excellent academic record.