Job Summary The Lead Data Scientist will lead the next generation of enterprise AI innovation across traditional machine learning, Generative AI, Agentic AI, intelligent automation, and AI-powered digital experiences. The role will define and execute AI strategy while leading the design, development, deployment, and continuous improvement of scalable AI solutions, including enterprise copilots, RAG-based knowledge systems, AI agents, intelligent workflow automation, and advanced predictive analytics. The position will partner with business leaders, product teams, architects, cybersecurity, and engineering teams to translate emerging AI capabilities into practical business solutions while establishing scalable frameworks, governance standards, and AI best practices. Key Responsibilities • Define and drive AI strategy across Machine Learning, Generative AI, Agentic AI, and Intelligent Automation initiatives. • Lead the design and delivery of enterprise-scale Generative AI applications, RAG platforms, conversational AI solutions, enterprise chatbots, AI copilots, virtual assistants, multi-agent systems, and knowledge discovery solutions. • Architect AI systems that integrate Large Language Models (LLMs), enterprise knowledge repositories, APIs, and business workflows while ensuring scalability, security, and governance. • Evaluate emerging AI technologies, foundation models, frameworks, orchestration platforms, and agentic architectures to determine strategic fit. • Lead AI product development from ideation through deployment, including experimentation, prototyping, productionization, monitoring, and continuous improvement. • Establish best practices and standards for LLMOps, AI governance, prompt engineering, model evaluation, AI safety, observability, and responsible AI. • Partner with business stakeholders to identify high-value AI opportunities and translate business challenges into AI-powered solutions. • Design and oversee RAG pipelines, vector databases, semantic search architectures, and knowledge management solutions. • Guide the development of AI-enabled products leveraging structured and unstructured data sources. • Collaborate with security, privacy, legal, and risk teams to ensure AI solutions meet regulatory, governance, and compliance requirements. • Mentor and develop data scientists, AI engineers, architects, and technical leaders while fostering innovation, experimentation, and continuous learning. • Communicate AI strategy, solution architectures, business value, and technical insights to executive leadership and non-technical stakeholders. Required Qualifications • Bachelor's degree from an accredited college or university and/or equivalent relevant experience. • 10+ years of experience in Artificial Intelligence, Data Science, Machine Learning, Software Engineering, or related disciplines. • Demonstrated experience delivering enterprise-scale Generative AI and Machine Learning solutions from concept through production. • Deep expertise in Large Language Models (LLMs), Generative AI architectures, Retrieval-Augmented Generation (RAG), prompt engineering, and AI orchestration frameworks. • Strong experience designing AI applications using technologies such as Azure AI, OpenAI, Anthropic, LangChain, Semantic Kernel, AutoGen, CrewAI, MCP, vector databases, and related AI ecosystems. • Strong understanding of Agentic AI patterns, including planning, orchestration, memory, tool use, workflow automation, and multi-agent systems. • Experience implementing AI governance, model evaluation, AI observability, security controls, and responsible AI frameworks. • Strong cloud expertise in Azure, AWS, or GCP, including AI platform services and production deployment architectures. • Advanced Python development skills and experience building scalable AI applications and APIs. • Experience working with structured and unstructured data, knowledge repositories, search platforms, and document intelligence solutions. • Proven ability to balance innovation with governance, risk management, security, and operational excellence. Preferred Qualifications • Master's degree, MBA, PhD, or CFA designation.