Decision Science Manager Artificial Intelligence

Job description

<p><p><b>Job Description</b><br/><br/><b>Job Title Ind & Func AI Decision Science Manager - S&C GN</b><br/><br/><b>Management Level : 7 - Manager</b><br/><br/><b>Location : Open</b><br/><br/><b>Must have skills : </b><br/><br/>- Generative AI, Agentic AI, Model Context Protocol (MCP), Large Language Models (LLMs), Multi-Agent Systems, Python, SQL, AI Agent Orchestration, Machine Learning,<br/><br/><b>- Good to have skills : </b> AI Refinery, LangChain, LlamaIndex, AutoGen, Crew AI, Spark, Cloud Platforms (AWS, Azure, GCP), NLP, Computer Vision, Vector Databases, RAG (Retrieval-Augmented Generation), Function Calling, Tool Integration<br/><br/>- Experience : Minimum 8 years of experience in AI/ML, with demonstrated expertise leading teams in Generative AI application and agentic system delivery, preferably within a consulting or client-facing environment<br/><br/>- Educational Qualification : Bachelor's or Master's degree (BE/BTech/MBA/MS) in Statistics, Computer Science, Mathematics, AI/ML, or related disciplines with an excellent academic record<br/><br/>Job Summary : As an AI Decision Science Manager, you will lead cross-functional teams in the design, development, and deployment of advanced AI agents and multi-modal AI solutions that autonomously execute complex business workflows.

You will be responsible for defining and implementing Gen AI and agentic AI strategies for clients, ensuring successful delivery of large-scale AI initiatives.

Your expertise will drive innovation, build client relationships, and shape the roadmap for autonomous AI-driven business transformation<br/><br/><b>Job Qualifications : & Responsibilities : </b></p><p><br/>Strategic Leadership & Project Delivery : </p></p><p><br/></p><p>- Oversee the end-to-end lifecycle of AI projects, from requirements gathering and solution architecture to deployment and post-implementation support<br/><br/></p><p>- Provide thought leadership and guidance to consultants and engineers on cutting-edge Gen AI and Agentic AI technologies<br/><br/></p><p>- Define and communicate a strategic vision for AI agent solutions, ensuring alignment with client business objectives<br/><br/>Client & Stakeholder Engagement : </p><p><br/></p><p>- Act as a trusted advisor to clients, translating complex AI concepts into actionable business solutions<br/><br/></p><p>- Drive discussions on Gen AI best practices, risk management, AI safety, and governance<br/><br/>Advanced Generative AI & Agentic System Development :</p><p><br/>- Design and implement sophisticated AI agents using frameworks like AI Refinery, LangChain, AutoGen, CrewAI, and custom agentic architectures<br/><br/></p><p>- Develop multi-agent systems that can collaborate, negotiate, and execute complex workflows autonomously<br/><br/></p><p>- Implement Model Context Protocol (MCP) integrations for seamless communication between AI systems and external tools/APIs<br/><br/></p><p>- Build and deploy Generative AI applications with advanced reasoning, planning, and execution capabilities<br/><br/>Leverage Advanced Data Science Techniques : </p><p><br/></p><p>- Develop solutions using Computer Vision, Machine Learning, and Large Language Models (LLMs).<br/><br/></p><p>- Define data requirements, clean, aggregate, analyze, and interpret data while conducting data quality assessments.<br/><br/>Develop and Implement AI Models : <br/><br/></p><p>- Build and deploy AI models and Generative AI applications.<br/><br/></p><p>- Train and fine-tune LLMs using large-scale datasets to optimize performance and accuracy.<br/><br/></p><p>- Evaluate model performance and implement iterative improvements.<br/><br/>Solution Integration and Deployment : <br/><br/></p><p>- Collaborate to integrate AI solutions into end-to-end workflows, ensuring scalability.<br/><br/></p><p>- Utilize cloud platforms like AWS, Azure, or GCP for model development and deployment.<br/><br/>Innovation and Knowledge Sharing : <br/><br/></p><p>- Stay updated on advancements in AI and Data Science, exploring innovative techniques and frameworks.<br/><br/></p><p>- Document methodologies and findings for effective knowledge sharing.<br/><br/><b>Professional & Technical Skills : </b><br/><br/>- Must To Have Skills : Expert proficiency in Generative AI, Agentic AI Systems, Model Context Protocol (MCP), LLMs, Multi-Agent Systems, Python, SQL, AI Agent Orchestration frameworks.<br/><br/>- Cloud & Infrastructure : AWS/Azure/GCP, Docker, Kubernetes, Spark, MLOps pipelines for agentic systems<br/><br/>- Specialized Knowledge : NLP, Computer Vision, Reinforcement Learning for agent training, Multi-modal AI systems.

Experience in developing and AI/ML models.<br/><br/>- The ideal candidate will possess deep expertise in agentic AI systems with a proven track record of building autonomous AI solutions that can execute complex business workflows<br/><br/>- Strong understanding of AI safety, alignment, and governance principles for autonomous systems<br/><br/>- Experience with enterprise-grade AI agent deployments and production system management<br/><br/>This position is based at our Gurugram office with opportunities to lead cutting-edge AI innovation projects<br/></p><br/></p> (ref:hirist.tech)

Required Skill Profession

Mathematical Science Occupations