Manager, Forward-Deployed AI Engineer (AI Mobilization & Transformation)

Join Mastercard as a Manager, Forward-Deployed AI Engineer, where you will lead AI transformation initiatives, partner with business units to identify high-value opportunities, and develop production-grade AI solutions. You will embed within business units, translate business challenges into practical AI applications, and create reusable playbooks and training assets. Success will be measured by the number of teams equipped to leverage AI independently and the measurable business outcomes achieved.

• Identifying high-value opportunities for AI implementation and leading AI transformation engagements.
• Building and deploying production-ready AI solutions, and creating reusable playbooks and training assets.
• Coaching and mentoring teams to independently leverage AI, and establishing a "train-the-trainer" model for sustainable capability.
• Demonstrated ability to build relationships and influence stakeholders across technical and business teams
• Comfortable working directly with business stakeholders to identify opportunities and redesign workflows
• Experience supporting cross-functional initiatives that combine AI adoption, workflow transformation, and capability development
• Experience building and deploying enterprise AI solutions that deliver measurable business outcomes
• Proven ability to influence organizational change through hands-on partnership and delivery
• Strong communication skills with the ability to explain AI concepts to both technical and non-technical audiences
• Ability to translate complex technical concepts into practical business value and adoption strategies
• Experience driving adoption of new technologies through hands-on engagement and coaching
• Financial services, payments, or enterprise transformation experience preferred
• Experience with Copilot Studio, Azure AI, GitHub Copilot, Claude Code, or equivalent platforms preferred
• Strong understanding of responsible AI, governance, risk management, and production monitoring practices
• Experience documenting and sharing repeatable patterns, practices, or implementation approaches
• Experience mentoring and developing technical talent through real-world project engagements
• Strong facilitation and coaching abilities, with experience educating technical and non-technical audiences
• Extensive software engineering experience with a track record of building and deploying production-grade systems
• Passion for developing others and creating sustainable capability within organizations
• Deep experience with AI technologies including LLMs, agent frameworks, RAG architectures, orchestration patterns, and AI application development