Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

Job Description: Senior Backend Engineer – AI Enablement (MCP Infrastructure & Channel Adapters)

About the Role

We are building an AI Enablement team focused on delivering a robust platform that empowers product and engineering teams to integrate AI capabilities rapidly, safely, and at scale. As a Senior Backend Engineer, you will be responsible for designing and implementing core components of our Model Context Protocol (MCP) infrastructure, building channel adapters, and enabling seamless integration with Large Language Model (LLM) tools and workflows.

This role requires a strong engineering foundation, a platform-team mindset, and the ability to build high‑quality, test‑first systems that other teams can depend on.

Key Responsibilities

Platform Engineering & MCP Infrastructure

• Design, develop, and maintain backend services powering the MCP platform including tool registries, adapters, execution runtimes, and orchestration layers.
• Build and evolve channel adapters that connect AI systems to external data sources, APIs, and enterprise services.
• Ensure reliability, observability, and operational excellence across all components.

Test-First Engineering

• Practice strict test-first development: TDD by default, with high-quality unit, integration, and contract tests.
• Drive engineering rigor and promote test-first culture within the team.

LLM & Tooling Integration

• Apply practical understanding of LLM fundamentals—tokens, context windows, tool descriptions, prompt structures—to build effective and efficient integrations.
• Implement and optimize MCP tool designs that allow other teams to create and consume AI functionality safely.

Platform Mindset & Collaboration

• Work closely with cross-functional engineering groups, understanding their needs and enabling them to deliver faster.
• Measure success by what other teams ship through the platform, not just what the AI Enablement team builds.
• Contribute to documentation, platform SDKs, and examples that lower adoption friction.

Required Qualifications

• Strong expertise in .NET (C#), with deep knowledge of backend development patterns, async programming, networking, and distributed systems.
• Proven experience delivering production-grade platforms, APIs, or high-scale services.
• Test-First mindset: TDD, contract testing, mocking strategies, and CI-driven quality gates.
• Working knowledge of LLMs including:
  • Tokens & context window limits
  • Tool descriptions & invocation patterns
  • Prompt and response schema design
• Ability to build quickly and iterate without requiring deep theoretical AI expertise.
• Excellent collaboration skills with a service-oriented mindset.

What Success Looks Like

• Other teams ship AI-powered features faster and more safely because of the infrastructure you build.
• AI tools are easy to integrate, observable, testable, and reliable.
• MCP-based components scale seamlessly across multiple teams and use cases.
• Engineering quality remains consistently high because of your test-first approach.

Preferred Qualifications

• Experience with Model Context Protocol (MCP) or similar tool/agent frameworks.
• Familiarity with event-driven architectures, streaming platforms, or asynchronous pipelines.
• Exposure to AI ecosystems: vector stores, embeddings, RAG, or agent frameworks.
• Experience building internal developer platforms or enablement tooling.

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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