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.
Job DescriptionAbout the Role:
We are looking for a Staff Platform Architect to join our Data & AI Platform Architecture team. We are a small, high-use group that shapes technology strategy across analytics products, AI/ML enablement, and data infrastructure at enterprise scale.
This is a role for someone with deep fundamentals in data, analytics, and MLOps platforms. You should also know how to evolve them to serve both humans and AI agents, internal and external, with equal thoughtfulness.
You will extend and evolve a set of existing platforms including our MLOps infrastructure, batch platform, analytics stack, and managed analytics offerings, while leading greenfield design of our AI-ready data foundation. You will report to the Sr. Director of Platform Engineering
What you'll do here
- Evolve our existing batch, analytics and MLOps platforms improving reliability, cost, and operational efficiency.
- Develop the infrastructure for our semantic and ontology layers. (including authoring and governance tooling, lifecycle management, and catalog integration)
- Design the usage infrastructure that makes these layers usable by any downstream consumer, including BI tools, ML pipelines, AI agents, internal users and client-facing products
- Design agent-driven data access patterns, including permission-aware semantic discovery, identity federation for AI workloads, and APIs that expose platform capabilities to LLM-based agents.
- Ensure shared platform capabilities translate cleanly into client-facing products.
- Guide technology adoption across engineering teams by making the right architectural choices well-reasoned and easy to follow.
- Lead focused prototyping and R&D efforts with analytics product and engineering teams to validate new AI and analytics capabilities before broader platform investment.
- Mentor engineers across the organization in your areas of expertise, with a focus on first-principles thinking, system design, and product awareness.
- 10+ years of software engineering experience, with a deep focus on data platforms, analytics infrastructure, and AI/ML systems at enterprise scale.
- Bachelor's Degree or higher in science, technology, engineering or related field
- Experience building or operating MLOps platforms from data access and feature engineering through model deployment and monitoring.
- Experience with data modeling, metadata, lineage, and data governance
- Hands-on experience with AI agent-based architectures, in the context of governed data access, semantic discovery, and retrieval over enterprise data assets.
- Experience with distributed computing, cloud-native infrastructure, and the cost and operational dynamics of running large-scale data workloads on public cloud (AWS preferred).
- Comfort with infrastructure as code and operating production workloads
- Experience influencing architectural decisions at scale, across teams and departments
- Experience building enterprise-scale data and MLOps platforms on Databricks
- Experience designing federated catalog architectures that deliver governed, unified data access across existing platforms and data silos.
- Experience with security, compliance and governance considerations for AI/ML workloads, including data residency, access control and audit requirements.
- Background in credit risk, financial services, or other regulated data domains where governance and compliance constraints shape platform design.
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
- #LI-Remote
Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why.
Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. This position is also eligible for a variable pay opportunity and a comprehensive benefits package.
Recruitment Fraud Awareness - 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 an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.
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.
Skills Required
- 10+ years of software engineering experience focused on data platforms, analytics infrastructure, and AI/ML systems at enterprise scale.
- Bachelor's Degree or higher in science, technology, engineering, or related field.
- Experience building or operating MLOps platforms from data access and feature engineering through model deployment and monitoring.
- Experience with data modeling, metadata, lineage, and data governance.
- Hands-on experience with AI agent-based architectures, governed data access, semantic discovery, and retrieval over enterprise data assets.
- Experience with distributed computing, cloud-native infrastructure, and operational dynamics of large-scale data workloads on public cloud.
- AWS experience (preferred).
- Comfort with infrastructure as code and operating production workloads.
- Experience influencing architectural decisions at scale across teams and departments.
- Experience building enterprise-scale data and MLOps platforms on Databricks.
- Experience designing federated catalog architectures to deliver governed, unified data access across platforms and silos.
- Experience with security, compliance, and governance for AI/ML workloads, including data residency, access control, and audit requirements.
- Background in credit risk, financial services, or other regulated data domains where governance and compliance shape platform design.
Experian Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Experian and has not been reviewed or approved by Experian.
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Healthcare Strength — Medical and dental coverage is described as strong, with expanded mental health resources and telemedicine options. Coverage includes inclusive services such as gender transition and fertility support.
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Leave & Time Off Breadth — Time-off offerings are generous, including substantial PTO/vacation, paid holidays, and paid volunteer days with options to purchase additional leave. Parental leave is available for birth and non-birth parents alongside flexible working arrangements that support work-life balance.
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Retirement Support — Retirement programs include a 401(k) with company matching and contributory pension schemes in some regions. These elements complement base pay and bonuses to form a competitive total rewards package.
Experian Insights
What We Do
Experian unlocks the power of data to create opportunities for consumers, businesses and society. During life’s big moments – from buying a home or car, to sending a child to college, to growing a business exponentially by connecting it with new customers – we empower consumers and our clients to manage data with confidence so they can maximize every opportunity. We gather, analyse and process data in ways others can’t. We help individuals take financial control and access financial services, businesses make smarter decision and thrive, lenders lend more responsibly, and organizations prevent identity fraud and crime. For more than 125 years, we’ve helped consumers and clients prosper, and economies and communities flourish – and we’re not done. Our 20,600 people in 43 countries believe the possibilities for you, and our world, are growing. We’re investing in new technologies, talented people and innovation so we can help create a better tomorrow. About Experian: Bringing data to life requires creativity, passion, flexibility and expertise. We want you to share in our success. That's why we offer rewards that recognise great performance. Working in a culture of collaboration, achievement and respect we will give you the support and encouragement you need to develop your skills and talents and progress your career. Everyday our people bring enthusiasm, innovation and inspiration to work and if this sounds like you connect with us at Experian.
