AI Engineering Manager

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

AI Engineering ManagerOverview
Mastercard's AI Center of Excellence (AI COE) is seeking an AI Engineering Manager to lead a team building production grade Agentic AI and traditional AI/ML solutions across the breadth of Mastercard's business. You will own delivery end to end—from architecture and experimentation to secure, compliant, scalable deployment—partnering closely with business, product, design, security, risk, and platform teams. This is a hands-on leadership role that combines technical depth, people leadership, and delivery to accelerate AI impact while upholding production grade standards for reliability, privacy, and Responsible AI.

The Role:

• Hire, develop, and retain a high performing team of AI engineers (LLM/ML, full stack, platform/MLOps, LLMOPs, evals) with clear growth paths, coaching, and inclusive practices.

• Establish engineering rituals (design reviews, postmortems, chapter forums) and uphold high bars for code quality, testing, security, and documentation.

• Define technical strategy and reference architectures for Agentic AI solutions and traditional AI/ML solutions

• Guide teams from POC to production: requirements, solution design, backlog, sprint execution, integration, performance, and operational readiness.

• Drive platform thinking—build reusable Agentic AI services, SDKs, and patterns for retrieval, orchestration, guardrails, evaluation, and observability.

• Lead design and build of Agentic AI solutions for priority business workflows across all Mastercard's Business

• Implement RAG, function/tool calling, knowledge graph integrations, and domain adapters for enterprise contexts.

• Stand up evaluation frameworks (offline/online, human in the loop) for quality, safety, latency, and task success, champion prompt and policy versioning.

• Own CI/CD for models and prompts, feature stores, vector indices, and model/prompt registries.

• Ensure observability, content safety, and guardrails in production.

• Partner with data engineering on pipelines, Legal and Data & AI Governance teams for data contracts, and Data product managers for high quality, policy compliant datasets.

• Embed privacy by design, data minimization, and financial services grade security into architectures.

• Collaborate with Risk, Compliance, and Legal to meet obligations (e.g., PCI DSS, GDPR, SOC 2, ISO 42001), and to operationalize Responsible AI (transparency, fairness, human oversight, auditability).

• Establish model risk management processes.

• Partner with Product Managers to define outcomes, prioritize roadmaps, and validate user value through experimentation.

• Translate complex technical tradeoffs for non-technical stakeholders, influence investment decisions with clear ROI and risk framing.

• Drive enablement for internal customers and ensure measurable adoption.

• Plan for multi region, high availability deployments with disaster recovery, performance tuning, and cost optimization.
Core Competencies

• People Leadership: Builds inclusive, high trust teams; coaches engineers; sets clear goals; recognizes excellence.

• Delivery Excellence: Plans, sequences, and executes complex programs; removes roadblocks; delivers reliably.

• Technical Judgment: Weighs build/buy performance vs. cost, guardrails vs. UX; anticipates risks early.

• Customer Obsession: Anchors solutions in measurable user and business outcomes.

• Communication: Explains complex concepts simply; adapts message to executives, partners, and engineers.

• Adaptability: Learns fast, iterates, and scales what works; comfortable with ambiguity and emerging tech.

All About You:

• Bachelor's or Master's in Computer Science, Data Science, or related field (or equivalent practical experience).

• Highly experienced background in software/AI engineering, including multiple years managing engineering teams delivering production AI/ML or Agentic AI systems.

• Proven track record shipping enterprise grade AI solutions at scale (high availability, low latency, strong security, and compliance).

• Languages/Frameworks: Python, PyTorch/TensorFlow; modern microservices.

• GenAI/LLMs: Prompt engineering, RAG, function/tool calling, agent frameworks, vector databases, embeddings.

• Data & Platforms: Modern data stacks, event driven designs; experience with one or more major clouds and GPU/accelerator workflows.

• MLOps/LLMOps: CI/CD, model & prompt registries, feature stores, model serving, canary/AB, offline/online evals, observability, cost management.

• Security & Responsible AI: Secrets management, IAM, network isolation, policy enforcement; familiarity with content safety/guardrail tooling and Responsible AI practices.

• UX Collaboration: Ability to partner with design and research on human centered, accessible interfaces for AI infused workflows.

• Experience in payments/financial services or similarly regulated environments is highly preferred.

• Knowledge of PCI DSS, GDPR, ISO 42001, and model risk practices; prior work with sensitive data controls (PII, tokenization, redaction).

• Multi region/active deployments, SLA/SLO design, and incident response leadership.

• Vendor/platform evaluation and contract oversight for AI tooling and foundation models.

• Publications, patents, OSS contributions in ML/LLM/agents are a plus.

#AI1Mastercard 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 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.

Pay Ranges

San Francisco, California: $166,000 - $265,000 USDBoston, Massachusetts: $159,000 - $254,000 USDNew York City, New York: $166,000 - $265,000 USDPurchase, New York: $159,000 - $254,000 USDRemote - New York: $138,000 - $221,000 USD

Job Posting Window

Posting windows may change based on the volume of applications received and business necessity. Candidates are encouraged to apply expeditiously.

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