Staff Platform Architect, Data & AI

Job not on LinkedIn

🔥 3 minutes ago

🇺🇸 United States – Remote

💵 $133.1k - $239.6k / year

⏰ Full Time

🔴 Lead

🔙 Backend Engineer

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Experian

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1996

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Experian is a global leader in digital experience, technology, and transformation. They partner with recognized brands to enhance customer understanding, innovate product strategies, and implement agile technology solutions. With a focus on delivering superior customer experiences through AI, cloud architecture, and project management, Experian helps businesses streamline their operations and achieve their objectives effectively.

📋 Description

• 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.

🎯 Requirements

• 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