Staff Platform Architect, Data & AI

🕒 vor 8 Tagen

🇺🇸 Vereinigte Staaten – Remote

💵 $133.109 - $239.596 / Jahr

⏰ Vollzeit

🔴 Experte

🔙 Backend-Entwickler

🦅 H1B-Visum-Sponsor

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Experian

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10.000+ Mitarbeiter

Gegründet 1996

💼 Beratung

📣 Marketing

📦 Logistik

Consulting • Marketing • Logistics

Experian entfesselt die Kraft der Daten, um Chancen für Verbraucher, Unternehmen und die Gesellschaft zu schaffen. In den großen Momenten des Lebens – vom Kauf eines Hauses oder Autos über das Studium eines Kindes bis hin zum exponentiellen Wachstum eines Unternehmens durch die Vernetzung mit neuen Kunden – befähigen wir Verbraucher und unsere Kunden, Daten mit Zuversicht zu verwalten, damit sie jede Gelegenheit maximal nutzen können.

Beschreibung

• 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.

🎯 Anforderungen

• 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.

🏖️ Vorteile

• 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