Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation

Mastercard is hiring a Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation in New York, United States. Level rates it ; you can apply on Mastercard.

Level's read on this job

On Level's scale, this AI engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Claude, Copilot and Claude Code.
Level lists 931 other open roles at Mastercard.
The role was posted in the last few days.

AI in this role

ClaudeCopilotClaude Code

prompt-engineeringragai-safety

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re 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

Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation

Overview
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.

Reporting to the Director, Forward-Deployed AI Engineer - AI Mobilization & Transformation, this role combines deep technical expertise with change leadership. Rather than building solutions in isolation, you will work alongside business teams to solve real problems, demonstrate the art of the possible, and develop internal capability through hands-on engagement.

Success is measured not only by the solutions delivered, but by the number of leaders, engineers, analysts, and teams equipped to independently leverage AI, agents, and multi-agent systems in their daily work.

The Role
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.

All About You
• 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.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

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 Mastercard’s 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 Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part 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; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 02/07/2027. If the fill date has passed, Mastercard intends to fill this position as soon as possible.

Pay Ranges

Purchase, New York: $161,000 - $266,000 USD

Arlington, Virginia: $161,000 - $266,000 USD

Atlanta, Georgia: $140,000 - $231,000 USD

How we rate this

Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation at Mastercard rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation is an open job at Mastercard.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Purchase, New York.
The job was posted on November 9, 2026.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI SafetyClaudeCopilotClaude Code

Also common in AI engineer jobs at this level

Python SQL AI agents AWS Generative AI TypeScript

Pay

Typical AI engineer job: $185k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you think about the risk of an AI system in this kind of role failing silently?
What's a project where you used Claude hands-on?
Walk me through how you've used Copilot in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, AI Safety, Claude, and Copilot. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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