At a Glance
- Tasks: Lead the design and development of cutting-edge AI platforms at Mastercard.
- Company: Join Mastercard's AI Center of Excellence, a leader in innovative technology.
- Benefits: Enjoy competitive salary, health benefits, and opportunities for professional growth.
- Other info: Be part of a dynamic team fostering technical excellence and innovation.
- Why this job: Make a real impact by architecting enterprise-scale AI systems that shape the future.
- Qualifications: 15+ years in software and AI engineering with hands-on coding experience.
The predicted salary is between 80000 - 100000 £ per year.
The AI Center of Excellence is seeking a Senior Principal Agentic Platforms Architect to lead the technical vision, architecture, and hands‑on development of Mastercard's enterprise agentic AI platforms. This role demands deep, demonstrated expertise in building and shipping production‑grade AI and agentic systems at enterprise scale, combined with the architectural rigor required to operate within one of the most highly regulated and security‑conscious environments in the world. Reporting to senior leadership, you will own the end‑to‑end platform architecture for agentic AI systems, from runtime orchestration and governance infrastructure through to production deployment and operational lifecycle management. This is not a strategy‑only role. You will write code, review code, and hold the team to the highest standards of engineering excellence.
The right candidate has spent their career building AI systems that run in production, not prototypes, not proofs of concept, but systems that operate at scale, under load, and under scrutiny.
Role- Serve as the principal technical authority for agentic AI platform architecture, owning the design and evolution of runtime environments, governance layers, orchestration engines, and multi‑tenancy infrastructure that support enterprise‑grade AI agent deployment.
- Lead hands‑on architecture and development of agentic systems, including agent orchestration frameworks, tool and model integration layers, policy enforcement engines, guardrail systems, behavioral monitoring pipelines, and evaluation infrastructure.
- Design and implement scalable, resilient platform architectures that support multi‑agent coordination, A2A communication protocols, memory governance, and real‑time observability across distributed deployments.
- Drive the technical strategy for model integration and abstraction, enabling model‑agnostic agent execution across multiple providers while enforcing cost optimization, routing intelligence, and governance controls at the platform level.
- Architect and build API‑first platform interfaces that enable both internal teams and external consumers to build, deploy, govern, and operate AI agents through programmatic, language‑agnostic access patterns.
- Define and enforce engineering standards, code quality practices, and architectural governance across the platform engineering team, ensuring every component meets production‑grade requirements for security, resilience, performance, and compliance.
- Provide deep technical leadership on agentic AI design patterns, including retrieval‑augmented generation, tool calling via Model Context Protocol, multi‑step orchestration, human‑in‑loop workflows, and autonomous decision‑making architectures.
- Act as a trusted technical advisor to senior leadership, translating complex platform architecture decisions into clear, business‑oriented language that supports informed decision‑making at the executive level.
- Mentor and develop a high‑performing engineering team, fostering a culture of technical excellence, intellectual honesty, rigorous code review, and continuous improvement.
- Produce and maintain authoritative architectural documentation, including system design documents, architecture decision records, and integration specifications that meet Mastercard's engineering principles and security standards.
- 15+ years of hands‑on experience in software engineering and AI engineering, with a significant and demonstrable portion spent designing, building, and shipping AI and machine learning systems to production at enterprise scale.
- Proven track record of architecting and delivering agentic AI systems, autonomous agents, multi‑agent orchestration platforms, or AI‑powered automation systems that operate in production with real users, real data, and real consequences.
- Deep hands‑on coding proficiency. You write production code, you review production code, and you hold others to the same standard. This is a building role, not a diagram‑drawing role.
- Advanced expertise in Python and modern AI/ML frameworks, with hands‑on experience across agentic toolkits such as LangChain, LangGraph, CrewAI, or equivalent orchestration frameworks.
- Strong architectural experience with cloud‑native platforms including AWS, Databricks, and Kubernetes, with demonstrated ability to design for high availability, fault tolerance, and horizontal scalability.
- Deep understanding of AI governance, trust, and safety architectures, including guardrail systems, policy engines, behavioral analytics, evaluation frameworks, red‑teaming methodologies, and compliance mapping.
- Experience designing and building multi‑tenant platforms with fine‑grained access control, workspace isolation, and enterprise‑grade identity and authorization systems.
- Proven ability to design API‑first architectures, RESTful interfaces, and SDK abstractions that serve both internal platform teams and external consumers.
- Strong understanding of data architectures including Delta Lake, data lakehouse patterns, vector databases and retrieval‑augmented generation pipelines.
- Demonstrated experience with tool calling architectures and model‑agnostic integration patterns across multiple LLM providers.
- Exceptional communicator who can articulate deeply technical architecture decisions to engineering teams and translate complex platform concepts into business language for non‑technical stakeholders.
- Known for building trust, holding high standards, and mentoring engineers. You make the people around you better. Motivated by hard problems, not titles. You bring intellectual curiosity, resilience, and relentless energy to complex technical challenges.
- Bachelor's degree in Computer Science, Engineering, or a related field. Advanced degree preferred but not required if the experience speaks for itself.
- 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.
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
Senior Principal Agentic Platforms Architect in London employer: Mastercard
As a Senior Site Reliability Engineer at Connex, you will be part of a dynamic team dedicated to maintaining the UK's national payment infrastructure, where innovation and collaboration are at the forefront of our work culture. We offer a supportive environment that prioritises continuous improvement and professional growth, alongside competitive benefits and a commitment to work-life balance. Join us in making a meaningful impact in the financial services sector while enjoying the unique advantages of working in a cutting-edge technology space.
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We think this is how you could land Senior Principal Agentic Platforms Architect in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Mastercard or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Tap into Online Developer Communities
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We think you need these skills to ace Senior Principal Agentic Platforms Architect in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Mastercard.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Mastercard and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Mastercard
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Mastercard uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.