[Hiring] Staff Platform Architect, Data & AI @Experian

Role Description

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.

Qualifications

• 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

• 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: Experian Benefits