Staff Platform Architect, Data & AI (Remote)

Google Chrome Microsoft Edge Apple Safari Mozilla Firefox Staff Platform Architect, Data & AI (Remote)Full-timeEmployee Status: RegularRole Type: HomeJob Posting - Salary Range: $133,109 - $239,596Department: TechnologyFlexible Time Off: 20 DaysSchedule: Full TimeShift: Day Shift Compensation: USD 137102 - USD 246784 - yearlyCompany DescriptionExperian 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 hereEvolve 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 productsDesign 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.Qualifications10+ 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 fieldExperience building or operating MLOps platforms from data access and feature engineering through model deployment and monitoring.Experience with data modeling, metadata, lineage, and data governanceHands-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 workloadsExperience influencing architectural decisions at scale, across teams and departmentsExperience building enterprise-scale data and MLOps platforms on DatabricksExperience 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...