๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐ ๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ญ๐ฎ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฎ๐ณ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ญ๐ฎ-๐ฎ๐ณ ๐๐ฃ๐) Experience: 7+ yrs Location: Pune As the AI Lead / Manager, you will collaborate with cross-functional teams, including Sales, Marketing, Supply Chain, Finance, HR, Customer Service, and IT, to identify business challenges and translate them into scalable AI-driven solutions. You will be responsible for defining the AI roadmap, establishing an AI Centre of Excellence (CoE), implementing responsible AI practices, and building internal capabilities to support long-term digital transformation. The role also involves leading AI talent, managing technology partners, and ensuring measurable business outcomes through successful AI adoption. Requirements Key Responsibilities โข AI Strategy & Roadmap: Develop and execute the enterprise AI and GenAI roadmap aligned with business objectives. Identify high-value use cases, build business cases, and define implementation priorities based on ROI and business impact. โข AI & GenAI Solution Delivery: Lead AI/ML initiatives from ideation and POC to production deployment. Drive solutions using machine learning, predictive analytics, NLP, LLMs, RAG, AI agents, and intelligent automation. โข Business Collaboration: Partner with business and technology stakeholders to identify opportunities, translate business requirements into AI solutions, and drive adoption across functions. โข Solution Architecture & Optimization: Collaborate with IT and data engineering teams to design scalable, secure, and reliable AI solutions. Establish standards for model development, deployment, monitoring, and continuous improvement. โข Data Governance & Responsible AI: Define frameworks for AI governance, data privacy, model risk management, security, explainability, and regulatory compliance. โข AI Centre of Excellence: Establish and strengthen the AI CoE by developing reusable frameworks, best practices, governance mechanisms, and a structured pipeline of AI initiatives. โข Team Leadership: Build, mentor, and lead AI, Data Science, and Analytics teams. Manage external consultants, technology partners, and vendors while evaluating emerging AI platforms and tools. โข Business Impact & Adoption: Track AI performance through measurable KPIs, including ROI, productivity improvements, process efficiency, solution accuracy, user adoption, and POC-to-production conversion. โข Executive Stakeholder Management: Present AI strategies, investment proposals, progress updates, and business outcomes to senior leadership. What Makes You a Great Fit? โข Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Statistics, Mathematics, or a related field. An MBA or business-oriented qualification is an added advantage. โข 7โ10 years of relevant experience in AI, Machine Learning, Data Science, Advanced Analytics, or Digital Transformation. โข Proven experience leading AI/ML projects from business problem identification through development, deployment, and production scaling. โข Strong expertise in Generative AI, LLMs, NLP, predictive analytics, RAG, and AI agent frameworks. โข Hands-on proficiency in Python and relevant AI/ML libraries, along with experience using cloud AI platforms such as AWS, Azure, or GCP. โข Good understanding of modern data architectures, APIs, vector databases, MLOps, model deployment, and AI monitoring. โข Experience working with cross-functional stakeholders, managing AI teams, and coordinating with external technology partners or consultants. โข Knowledge of AI governance, responsible AI principles, data security, privacy, and model risk management. โข Strong strategic thinking and business acumen, with the ability to translate AI capabilities into measurable business value. โข Excellent communication, stakeholder management, problem-solving, and people leadership skills. โข A proactive, innovation-driven mindset with the ability to move AI initiatives from experimentation to scalable, production-ready solutions and drive enterprise-wide adoption.