\\\\Our Purpose\\\\ \Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, were helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.\\ \\\\Title and Summary\\\\ Managing Consultant, AI Subject Matter Expert - Advisors & Consulting Services Managing Consultant Strategy & Transformation AI Specialist Advisors & Consulting Services Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. Our Advisors & Consulting Services team combines traditional management consulting with Mastercards rich data assets, proprietary platforms, and technologies to provide clients with powerful strategic insights and recommendations. Our teams work with a diverse global customer base across industries, from banking and payments to retail and restaurants. The Advisors & Consulting Services group has five specializations: Strategy & Transformation, Performance Analytics, Business Experimentation, Marketing, and Program Management. Our Strategy & Transformation consultants lead clients through impactful decision-making as they tackle strategic, tactical, operational, and transformational business challenges. They apply a broad set of problem-solving techniques to improve the clients overall strategy, performance, and operations. Positions for different specializations and levels are available in separate job postings. Please review our consulting specializations to learn more about all opportunities and apply for the position that is best suited to your background and experience: We are seeking an experienced Consulting Project Manager with deep, hands-on expertise in Generative AI and Agentic AI systems to lead end-to-end delivery of AI transformation initiatives for clients. This role sits at the intersection of AI engineering, product thinking, and consulting deliveryowning outcomes from use-case definition through production deployment. The ideal candidate has personally built, tested, and deployed LLM-powered solutions, understands modern agent frameworks, and can credibly engage both C-suite stakeholders and engineering teams Key Responsibilities Lead client engagements focused on GenAI and agentic AI solutions, from discovery and architecture through delivery and scale Translate business problems into LLM-driven and agent-based solutions (e.g., autonomous workflows, AI copilots, decision agents) Act as a hands-on delivery lead, reviewing prompts, agent logic, RAG pipelines, evaluation metrics, and deployment approaches Manage multi-disciplinary teams (AI engineers, data scientists, cloud engineers, UX) using agile delivery models Own client communication, roadmap definition, risk management, and value realization Ensure solutions meet security, governance, compliance, and responsible AI standards Support pre-sales by contributing to proposals, solution design, and client workshops Required Experience & Skills AI & Technical (Hands-On Mandatory) Strong, practical experience working with LLMs, such as: o OpenAI / Azure OpenAI, Anthropic, Gemini, or open-source models (LLaMA, Mistral, etc.) Hands-on experience with: o Prompt engineering and prompt optimization o RAG architectures (vector databases, embeddings, retrieval strategies) o Agentic frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, custom agent orchestration) Experience building and deploying multi-agent or tool-using systems (function calling, APIs, workflows) Familiarity with LLM evaluation, observability, latency/cost optimization, and hallucination mitigation Working knowledge of cloud AI stacks (Azure, AWS, or GCP) and modern MLOps / LLMOps practices Consulting & Delivery 812+ years of experience in consulting, digital transformation, or AI delivery roles Proven track record managing complex client engagements with senior stakeholders Strong ability to bridge business strategy and technical execution Experience delivering AI solutions in banking, retail, telecom, or regulated industries is a strong plus Preferred Qualifications Background as an AI engineer, data scientist, or solution architect before moving into project/program leadership Experience defining AI operating models and scaling GenAI across an enterprise Exposure to agentic commerce, autonomous decisioning, or AI-driven operations Certifications in cloud platforms or AI/ML (nice to have, not mandatory) What Success Looks Like Clients trust you as a credible AI practitioner, not just a project manager AI solutions move from POC to production, delivering measurable business value Teams ship robust, scalable agentic systems, not demos You help shape the firms AI consulting offerings and delivery standards \\\\Corporate Security Responsibility\\\\ All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: \\+ Abide by Mastercards security policies and practices; \\+ Ensure the confidentiality and integrity of the information being accessed; \\+ Report any suspected information security violation or breach, and \\+ Complete all periodic mandatory security trainings in accordance with Mastercards guidelines.

The role requires strong, practical experience working with Large Language Models (LLMs) such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models like LLaMA and Mistral. Hands-on experience with prompt engineering, prompt optimization, and RAG architectures, including vector databases, embeddings, and retrieval strategies, is mandatory. Proficiency in agentic frameworks like LangGraph, AutoGen, CrewAI, or Semantic Kernel, and experience building and deploying multi-agent or tool-using systems are also required. A working knowledge of cloud AI stacks (Azure, AWS, or GCP) and modern MLOps/LLMOps practices is necessary. The position also demands 8-12+ years of experience in consulting, digital transformation, or AI delivery roles, with a proven track record of managing complex client engagements and bridging business strategy with technical execution.