Manager, Forward-Deployed AI Engineer

Mastercard

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Purchase, NYArlington, VAAtlanta, GA
Salary
$161,000–$266,000 / yr
Posted
11 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $212k
This role $214k
$148k most similar roles pay here $279k

This role pays more than 52% of similar roles. Most pay $177,675–$246,150 — the shaded band above. At the midpoint, this role pays about $214k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Mastercard

Mastercard is a global technology company in the payments industry, processing transactions between financial institutions and merchants using its extensive network of credit, debit, and prepaid card products. Industry: Payments Technology & Financial Services

Mastercard currently has 116 open roles on FindRole.

Listed pay typically runs $122,000–$207,000 across 104 roles with salary data.

Most-posted roles

View all roles at Mastercard

At a glance

TL;DR · Manager, Forward-Deployed AI Engineer

Manager, Forward-Deployed AI Engineer — AI Mobilization & Transformation serves as an embedded leader within business units to identify high-value opportunities and develop production-grade AI solutions. This role focuses on transforming workflows by designing and deploying AI assistants, multi-agent systems, and orchestration frameworks while building internal capabilities through hands-on coaching and "train-the-trainer" models. You will translate complex business challenges into practical applications of LLMs, RAG architectures, and agentic flows to automate decision processes. The role requires expertise in Copilot Studio, Azure AI, GitHub Copilot, Claude Code, and other orchestration platforms. Key responsibilities include creating reusable playbooks, establishing reference architectures, and promoting responsible AI governance. You will work to move teams from experimentation to operationalized solutions, ultimately ensuring that internal partners can independently leverage AI tools and techniques to drive measurable productivity gains across the enterprise.

What you'll do

  • Identify and design high-impact AI use cases to solve specific business workflow and productivity challenges.
  • Develop production-ready AI assistants, agents, and multi-agent orchestration frameworks using tools like Copilot Studio and Azure AI.
  • Translate complex technical AI concepts into practical applications and measurable business outcomes for non-technical stakeholders.
  • Conduct hands-on workshops on prompt engineering, agent design, and AI-assisted development to train internal teams.
  • Create reusable playbooks, reference architectures, and implementation patterns to accelerate enterprise-wide AI adoption.
  • Establish a "train-the-trainer" model to empower local teams to manage and scale AI capabilities independently.
  • Document and share lessons learned, success stories, and emerging patterns to build an internal library of AI assets.

What we're looking for

  • 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 application development.
  • Experience building and deploying enterprise AI solutions that deliver measurable business outcomes.
  • Strong facilitation and coaching abilities to educate both technical and non-technical audiences.
  • Proven ability to influence organizational change through hands-on partnership and mentoring technical talent.
  • 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 with Copilot Studio, Azure AI, GitHub Copilot, Claude Code, or equivalent platforms (preferred); financial services or enterprise transformation experience (preferred).

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