Principal Agentic Platforms Architect

Posted 2 Hours Ago
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London, Greater London, England, GBR
Hybrid
Expert/Leader
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Lead the architecture and hands-on development of Mastercard’s enterprise agentic AI platforms. Own runtime orchestration, governance, multi-tenancy, model and tool integration, security, observability, evaluation, and production lifecycle management. Design scalable multi-agent systems, API-first capabilities, model-agnostic integrations, and AI safety controls. Establish engineering standards, conduct architecture and code reviews, advise executives, document technical decisions, and mentor engineers.
Summary Generated by Built In
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
Principal Agentic Platforms Architect
The AI Center of Excellence is seeking a Principal Agentic Platforms Architect to lead the technical vision, architecture, and hands-on development of Mastercard's enterprise agentic AI platforms. This role requires deep, demonstrated expertise building and shipping production-grade AI and agentic systems at enterprise scale, combined with the architectural rigor required in a highly regulated and security-conscious environment
Reporting to senior leadership, you will own the end-to-end platform architecture for agentic AI systems, spanning runtime orchestration, governance, model and tool integration, multi-tenancy, production deployment, and operational lifecycle management. This is a hands-on technical leadership role. You will write and review production code, establish engineering standards, and drive the team toward the highest levels of security, resilience, performance, and engineering excellence
Responsibilities
- Own the enterprise agentic AI platform architecture, including runtime environments, orchestration, governance, multi-tenancy, policy enforcement, guardrails, observability, evaluation, and production lifecycle management
- Lead hands-on architecture and development of scalable agentic systems, including multi-agent coordination, A2A communication, memory governance, tool calling, Model Context Protocol, human-in-the-loop workflows, and autonomous decision-making patterns
- Drive model and platform integration strategy, enabling model-agnostic execution across providers while establishing intelligent routing, cost optimization, abstraction layers, and enterprise governance controls
- Architect API-first platform capabilities that allow internal teams and external consumers to build, deploy, govern, and operate AI agents through secure, scalable, language-agnostic interfaces.
Set and enforce technical standards across the platform, including architecture, code quality, security, resilience, performance, compliance, and operational excellence. Provide rigorous technical direction through architecture reviews and code reviews
- Serve as the senior technical authority and advisor for agentic AI architecture, translating complex technical decisions into clear business and executive-level recommendations while mentoring engineers and strengthening the organization's technical capabilities
- Establish architectural governance and documentation, including system designs, architecture decision records, integration specifications, and engineering standards aligned with Mastercard's security and technology principles
All About You
- 12+ years of hands-on software and AI engineering experience, with substantial experience designing, building, and shipping enterprise AI/ML systems into production at scale
- Proven experience architecting production-grade agentic AI systems, autonomous agents, multi-agent platforms, or AI-powered automation operating with real users, real data, and real business impact
- Deep hands-on coding expertise, particularly in Python and modern AI/ML frameworks. Experience with agentic frameworks such as LangChain, LangGraph, CrewAI, or equivalent is highly valued
- Strong cloud-native architecture expertise across platforms such as AWS, Databricks, and Kubernetes, with a demonstrated ability to design highly available, fault-tolerant, secure, and horizontally scalable systems
- Deep expertise in AI governance, trust, and safety, including guardrails, policy engines, behavioral monitoring, evaluation, red teaming, compliance, and enterprise risk controls
- Experience building enterprise platforms and data architectures, including multi-tenant systems, fine-grained authorization, identity and access management, API-first architectures, data lakehouse patterns, Delta Lake, vector databases, and RAG pipelines
- Strong understanding of model-agnostic AI architectures and tool integration, including multi-provider LLM integration, tool calling, orchestration, and abstraction patterns
- Exceptional technical and executive communication skills, with the ability to influence senior stakeholders, simplify complex architecture decisions, and build alignment across engineering and business organizations
- Demonstrated technical leadership and mentorship, with a reputation for high standards, intellectual curiosity, resilience, and developing engineers into stronger technical leaders
- Bachelor's degree in Computer Science, Engineering, or a related field. An advanced degree is preferred but not required with equivalent experience
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.

Skills Required

  • 12+ years of hands-on software and AI engineering experience
  • Substantial experience designing, building, and shipping enterprise AI/ML systems into production at scale
  • Experience architecting production-grade agentic AI systems, autonomous agents, multi-agent platforms, or AI-powered automation
  • Deep hands-on coding expertise, particularly in Python and modern AI/ML frameworks
  • Experience with agentic frameworks such as LangChain, LangGraph, CrewAI, or equivalent
  • Cloud-native architecture expertise across AWS, Databricks, and Kubernetes
  • Expertise in AI governance, trust, and safety, including guardrails, policy engines, behavioral monitoring, evaluation, red teaming, compliance, and enterprise risk controls
  • Experience building enterprise platforms and data architectures, including multi-tenant systems, fine-grained authorization, identity and access management, API-first architectures, data lakehouse patterns, Delta Lake, vector databases, and RAG pipelines
  • Understanding of model-agnostic AI architectures and tool integration, including multi-provider LLM integration, tool calling, orchestration, and abstraction patterns
  • Exceptional technical and executive communication skills
  • Demonstrated technical leadership and mentorship
  • Bachelor's degree in Computer Science, Engineering, or a related field
  • Advanced degree

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support Retirement plans are presented as best-in-class with a high company match on 401(k) or local equivalents. Career materials and U.S. postings consistently highlight retirement matching as a standout feature.
  • Leave & Time Off Breadth U.S. postings describe generous paid time off including vacation, personal days, holidays, sick/safe time, and additional bereavement leave. A hybrid policy and a limited “work from elsewhere” option further support time away.
  • Parental & Family Support Company pages state a global minimum of 16 weeks of paid new-parent leave across birth, adoption, and foster, plus family-building assistance where permitted. Mental-health resources and caregiving supports are also emphasized.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

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

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

Typical time on-site: 3 days a week
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