Experian is hiring a Solution Engineer - Remote

Experian is looking for a Solutions Engineer who combines technical depth with client engagement skills to increase adoption of the Bureau Composer platform. This is a client-facing role at the intersection of solution architecture, AI-enabled decisioning, and revenue enablement. You will partner directly with clients, sales, and our teams to design scalable, data-driven solutions. These solutions address complex challenges across credit, fraud, identity, and decisioning use cases, with relevance to financial institutions. You will oversee the solution lifecycle for client engagements, translating requirements into production-ready solution designs that use APIs, microservices, cloud-native platforms, data integration patterns, and AI-enabled workflows. We ask that you have applied AI experience and the ability to position AI capabilities. Responsibilities - Lead discovery and requirements sessions with clients to define goals, technical requirements, data needs, and solution scope - Translate client needs into end-to-end solution designs using APIs, microservices, cloud infrastructure, data integration patterns, and AI-enabled workflows - Design and deliver scalable implementations using the Bureau Composer platform, including real-time decisioning workflows and both standard and custom solutions - Lead our client-facing solution delivery lifecycle including implementation planning, technical design leadership, and coordination across engineering, QA, DevOps, compliance, and project teams - Conduct technical presentations, demos, and workshops tailored to executive, business, and technical audiences - Support deployment, integration, and troubleshooting to ensure successful production rollout and ongoing solution optimization - Partner with sales and product teams to identify expansion opportunities, support solution strategy, and increase incremental revenue - Ensure solutions align with security, compliance, and data governance requirements, including FCRA, FACTA, IAM, explainability, and data protection considerations - Build and improve reusable solution patterns, accelerators, and technical strategies to support scale and consistency across implementations