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Principal Agentic Platforms Architect

Job in City Of London, Central London, Greater London, England, UK
Listing for: Mastercard
Full Time position
Listed on 2026-09-05
Job specializations:
  • Software Development
    Software Architect, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 150000 - 190000 GBP Yearly GBP 150000.00 190000.00 YEAR
Job Description & How to Apply Below
Location: City Of London

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 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.
Qualifications
  • 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 Lang Chain, Lang Graph, 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…
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