Staff Platform Architect, Data & AI

🕒 4 dias atrás

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $133.109 - $239.596 / ano

⏰ Tempo Integral

🔴 Especialista

🔙 Engenheiro Backend

🦅 Patrocina Visto H1B

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Experian

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1996

💼 Consultoria

📣 Marketing

📦 Logística

Consulting • Marketing • Logistics

A Experian libera o poder dos dados para criar oportunidades para consumidores, empresas e a sociedade.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• 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