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Director, Forward-Deployed AI Engineer - AI Mobilization & Transformation

Mastercard

Purchase, New York | Arlington, US$195k – $323konsite

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About this role

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

Director, Forward-Deployed AI Engineer - AI Mobilization & Transformation

Overview The Director, 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 VP of Organizational Readiness, 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. • Develop repeatable transformation approaches that can be scaled across multiple business units and functions. • Identify and prioritize high-value opportunities that accelerate enterprise AI adoption and capability growth.

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, 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 internal champions capable of independently driving AI adoption and solution delivery. • Promote knowledge sharing and adoption of best practices across teams and business units.

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. • Partner with engineering and business leaders to drive scalable adoption of agentic solutions across the enterprise. • Evaluate emerging AI capabilities and identify opportunities to apply them to business challenges.

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 and share best practices, reusable assets, and implementation patterns across engagements. • Drive continuous improvement of AI transformation approaches based on engagement outcomes and organizational learning.

All About You • 5+ years of 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 leading complex, cross-functional initiatives that combine technology adoption, organizational change, and business transformation. • Demonstrated ability

Salary insight

The midpoint of this range ($259k) is about 57% above the median disclosed salary for New York roles listed on ForgeApply ($165k across 7,345 jobs).

See full Machine Learning Engineer salary data for New York →

Based on live postings with disclosed pay on ForgeApply; refreshed daily. Not an estimate of this employer's offer.

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