Principal Platform Engineer, AI Native SDLC
Experian is hiring a Principal Platform Engineer, AI Native SDLC. Level rates it ; you can apply on Experian.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Claude, LangGraph and Claude Code.
- Level classifies it as a lead role.
- Level lists 395 other open roles at Experian.
- The role was posted in the last few days.
AI in this role
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.
At Experian, we believe great work happens when people come together. We're focused on attracting talent in and around our designated hub locations who are open to collaborating with colleagues in person. Aligning employees to these talent markets helps foster collaboration, strengthen team connections, and support long-term career growth within Experian. This is a hybrid role and you will report to the VP, Partner Solutions Engineering, and reside in or near one of our collaboration hubs:
Costa Mesa, CA; San Jose, CA; Allen, TX; Austin, TX; Franklin, TN; New York, NY; Schaumberg, IL; Washington, D.C.; Atlanta, GA; Boston, MA; Seattle, WA
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.
- 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
- Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html
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.
Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
How we rate this
Principal Platform Engineer, AI Native SDLC at Experian rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through how you've used Claude in your day-to-day work.
- What are the limits of LangGraph that you've run into, and how did you work around them?
- What's a project where you used Claude Code hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: AI agents, Claude, LangGraph, and Claude Code. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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