Principal Platform Engineer, AI Native SDLC

Overview

We are looking for an experienced and influential Principal AI Platform Engineer to lead the technical design of Experian's AI-native software development lifecycle. You will work on the developer platform that serves more than 5,000 engineers across our business units and regions, and define how AI agents, enterprise engineering knowledge and a governed marketplace come together to change how software is built.

You will report to the VP, AI Developer Platforms, and operate as a hands-on technical leader, influencing architecture and implementation across multiple teams. This is an individual contributor role with no direct reports.

You will

• Define the reference architecture and capability map for the AI-native SDLC, from requirements through deployment and incident response, including where agents act and where people approve.
• Develop the engineering knowledge subgraph that grounds AI agents in Experian's services, APIs, standards, architecture decisions and incident history.
• Build SDLC agents, such as pull request review, documentation, rollout risk, with evaluation, audit logging and least-privilege access.
• Design the AI marketplace where teams discover, contribute and reuse agents, MCP servers and skills, including trust tiers and the path from experimental to supported.
• Utilize thee Model Context Protocol as the standard interface so tools can be replaced without rebuilding the platform.
• Partner with security, enterprise AI, cloud and engineering teams on policy and data classification
• Measure adoption, productivity and quality with telemetry, and report outcomes the platform directly controls.
• Write architecture decision records that governance bodies can approve, and mentor engineers across the platform organization.

Qualifications & Requirements

• 10 or more years of software engineering experience, including at least 5 years building developer platforms or internal tooling at enterprise scale.
• 2+ years designing and running LLM-based or agentic systems in production, including multi-agent orchestration (such as LangGraph), evaluation, cost control, failure handling and human approval workflows for consequential actions.
• Hands-on experience with knowledge graph or hybrid graph and vector retrieval design, ontology modeling and data ingestion pipelines.
• Working knowledge of the Model Context Protocol, API design, event-driven integration, OAuth and workload identity
• Familiarity with the SDLC toolchain (Jira, Confluence, Git platforms, CI/CD, ServiceNow and OpenTelemetry).
• Understanding of AI governance and security in a regulated industry: data classification for model calls, prompt injection defenses, audit logging and least privilege.
• Experience with developer portals such as Backstage, InnerSource programs, rolling out coding agents such as Claude Code, or measurement frameworks such as DORA and SPACE
• #LI-Hybrid

Benefits/Perks

• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays

• Our uniqueness is that we celebrate yours.
• Experian's people first, inclusive and purpose-driven culture is multi award-winning.
• We have won World's Best Workplaces™ 2025 (Fortune Global Top 25), and Great Place To Work™ in 26 countries to name a few.

• Experian's recruitment process is conducted only through authorised channels.
• Recruitment communications will only be sent from an @ experian.com email address.
• Experian will never ask candidates to make any payment as part of a recruitment process.

• Our compensation reflects the cost of labor across several U.S. geographic markets.
• Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education.
• You will be eligible for a variable pay opportunity and a comprehensive benefits package.