Principal Agentic Platforms Architect

London Source: WhatJobs

See advert for pay

Overview

In this role you will lead the technical vision and hands-on development of Mastercard’s enterprise agentic AI platforms. You will own the end-to-end architecture for production-grade AI systems at enterprise scale within a security-conscious setting. You will translate complex decisions into clear guidance, mentor engineers, and establish engineering standards to drive security, resilience, and performance. You will collaborate with cross-functional teams to enable secure, multi-tenant, API-first platform capabilities and deliver impactful AI-enabled automation.

Responsibilities

Own enterprise agentic AI platform architecture including runtime environments, orchestration, governance, multi-tenancy, policy enforcement, guardrails, observability, and lifecycle management
Lead hands-on architecture and development of scalable agentic systems (multi-agent coordination, memory governance, tool calling, Model Context Protocol, human-in-the-loop workflows, autonomous decisions)
Drive model and platform integration strategy for model-agnostic execution across providers with intelligent routing, cost optimization, and governance controls
Architect API-first platform capabilities enabling internal teams and external consumers to build, deploy, govern, and operate AI agents via secure interfaces
Set and enforce technical standards across architecture, code quality, security, resilience, performance, and compliance
Provide technical direction through architecture and code reviews and act as senior advisor for agentic AI architecture
Establish architectural governance and documentation including system designs, ADRs, integration specs, and engineering standards
Mentor engineers and strengthen the organization’s technical capabilities

Key requirements

12+ years of hands-on software and AI engineering experience
Proven experience architecting production-grade agentic AI systems or AI-powered automation
Deep Python coding skills and experience with modern AI/ML frameworks
Experience with agentic frameworks such as LangChain, LangGraph, CrewAI or equivalents
Strong cloud-native architecture experience (AWS, Databricks, Kubernetes)
Expertise in AI governance, trust, safety, guardrails, policy engines, monitoring, and risk controls
Experience building enterprise platforms with multi-tenant data architectures, IAM, API-first designs, and data lakehouse patterns
Ability to communicate complex decisions to executives and stakeholders
Mentorship and technical leadership track record
Bachelor’s degree in Computer Science, Engineering, or related field; advanced degree preferred