# Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation **Company**: Mastercard **Location**: Purchase, New York, New York **Experience**: senior **Job type**: full-time **Salary**: $161,000 - $266,000 USD **Category**: Engineering **Industry**: Finance **Apply**: https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Purchase-New-York/Manager--Forward-Deployed-AI-Engineer---AI-Mobilization---Transformation_R-295497?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/job/manager-forward-deployed-ai-engineer-ai-14fa46cc-221/ ## Description The Manager, Forward-Deployed AI Engineer serves as Mastercard's embedded AI transformation leader, partnering directly with business units to identify high-value opportunities, develop production-grade AI solutions, and mobilize teams to adopt new ways of working. **Responsibilities** ### Mobilizing AI Adoption Through Bespoke Engagements - Embed within business units to identify strategic workflow, productivity, and decision-making opportunities where AI can create measurable value. - Lead AI Transformation Engagements that combine discovery, solution design, implementation, and capability building. - Build high-impact use cases that serve as showcase examples for broader organizational adoption. - Translate business challenges into practical applications of AI, agents, and multi-agent orchestration. - Create reusable playbooks, patterns, and training assets that accelerate adoption across the enterprise. - Partner with business leaders to demonstrate measurable outcomes and establish local AI champions. - Support the identification and delivery of high-value AI opportunities across business functions. - Contribute reusable assets and implementation patterns that accelerate future engagements. ### Building While Teaching - Design and deploy production-ready AI assistants, agents, and orchestration frameworks that solve real business problems. - Use each engagement as a live learning environment where business and technical teams learn modern AI practices through delivery. - Coach engineers, analysts, product managers, knowledge workers, and operational teams on AI-first ways of working. - Establish a "train-the-trainer" model that enables local teams to continue scaling capabilities after engagements conclude. - Facilitate hands-on workshops focused on prompt engineering, agent design, workflow automation, Copilot practices, and AI-assisted development. - Develop practitioners capable of independently applying AI tools and techniques within their teams. - Promote knowledge sharing and adoption of established AI best practices. ### Advancing Agentic Transformation - Architect and implement solutions leveraging Copilot Studio, Azure AI, agent frameworks, orchestration systems, and enterprise platforms. - Develop multi-agent solutions that automate complex business processes and decision flows. - Introduce modern engineering practices including AI-assisted software development, evaluation frameworks, observability, and governance. - Establish proven reference architectures and patterns that can be replicated across business units. - Help business teams evolve from experimentation to operationalized AI solutions. - Apply established AI patterns and frameworks to accelerate solution delivery and adoption. - Evaluate emerging AI capabilities and assist in translating them into practical business applications. ### Capturing and Scaling Organizational Learning - Document emerging patterns, successful use cases, implementation approaches, and lessons learned. - Build an enterprise library of AI-enabled workflows, agents, and transformation stories. - Identify adoption barriers and design interventions that accelerate organizational readiness. - Contribute to enterprise readiness metrics by measuring adoption, productivity gains, capability growth, and business impact. - Create a feedback loop between field engagements, engineering teams, and organizational readiness programs. - Capture reusable assets, implementation approaches, and best practices from engagements. - Share lessons learned to improve future AI transformation efforts across the organization. **Requirements** - Extensive software engineering experience with a track record of building and deploying production-grade systems. - Deep experience with AI technologies including LLMs, agent frameworks, RAG architectures, orchestration patterns, and AI application development. - Experience building and deploying enterprise AI solutions that deliver measurable business outcomes. - Strong facilitation and coaching abilities, with experience educating technical and non-technical audiences. - Comfortable working directly with business stakeholders to identify opportunities and redesign workflows. - Proven ability to influence organizational change through hands-on partnership and delivery. - Experience mentoring and developing technical talent through real-world project engagements. - Strong understanding of responsible AI, governance, risk management, and production monitoring practices. - Ability to translate complex technical concepts into practical business value and adoption strategies. - Experience supporting cross-functional initiatives that combine AI adoption, workflow transformation, and capability development. - Demonstrated ability to build relationships and influence stakeholders across technical and business teams. - Experience documenting and sharing repeatable patterns, practices, or implementation approaches. - Strong communication skills with the ability to explain AI concepts to both technical and non-technical audiences. - Experience driving adoption of new technologies through hands-on engagement and coaching. - Experience with Copilot Studio, Azure AI, GitHub Copilot, Claude Code, or equivalent platforms preferred. - Financial services, payments, or enterprise transformation experience preferred. - Passion for developing others and creating sustainable capability within organizations. **Success in This Role** Success is not measured by the number of agents you build. Success is measured by the number of teams that can build without you. You leave behind: - New organizational capability. - Repeatable AI patterns. - Trained champions and practitioners. - Demonstrated business value. - Sustainable adoption of AI-first ways of working. - Increased confidence and proficiency in applying AI across day-to-day work. - Reusable assets and implementation practices that accelerate future adoption. **Benefits** Mastercard benefits for full-time employees generally include: - Insurance (including medical, prescription drug, dental, vision, disability, life insurance) - Flexible spending account and health savings account - Paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave) - 80 hours of Paid Sick and Safe Time - 25 days of vacation time and 5 personal days, pro-rated based on date of hire - 10 annual paid U.S. observed holidays - 401k with a best-in-class company match - Deferred compensation for eligible roles - Fitness reimbursement or on-site fitness facilities - Eligibility for tuition reimbursement For more fresh new jobs, check out [yubhub.co](https://yubhub.co/). ## Skills ### Required - AI technologies - LLMs - agent frameworks - RAG architectures - orchestration patterns - AI application development - Copilot Studio - Azure AI ### Nice to have - GitHub Copilot - Claude Code - financial services - payments - enterprise transformation --- Source: [Apply at mastercard.wd1.myworkdayjobs.com](https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Purchase-New-York/Manager--Forward-Deployed-AI-Engineer---AI-Mobilization---Transformation_R-295497?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)