Senior Manager, Software Engineering - Remote

The Financial Services Division (FSD) Engineering team is looking for an Engineering leader. This leader must excel in a non-traditional environment, working with the latest of the Cloud, Big Data, and AI/GenAI ecosystem. Data is the currency in today's world, and in this role, you will be at the forefront of a digital and AI-driven transformation. Reporting to the Director of Software Development, you will lead the development and operations of our real-time API platform, a critical component that powers mission-critical integrations across our ecosystem. You will be responsible for designing, building, and scaling available, low-latency APIs. These APIs support millions of transactions per day. Additionally, you will guide the integration of AI capabilities and latest technologies into our platform, including Model Context Protocol (MCP) and Claude Skills.What you'll doYou will lead engineering teams building platform capabilities and solutions for our clients using Experian bureau data and other 3rd party data.You will build data pipelines at scale for our batch clients and integrating with 3rd party providers for our real-time clients.You will also advocate for using AI and GenAI technologies across the team, including LLM-powered services, agentic workflows, MCP-based integrations, and Claude Skills for extending agent capabilities.Platform OwnershipOversee the architecture, design, and implementation of real-time APIs with a focus on scalability, reliability, and latencyYou will create platform evolution, including modernization, observability, AI-enablement, and CI/CD best practicesTechnical StrategyCollaborate with partners to define the long-term vision and roadmap for the API platform, including how you will embed AI capabilities, MCP integrations, and Claude skills into the ecosystem.Ensure the team follows software engineering best practices including testing, code reviews, and documentationGuide the use of latest technologies that support real-time processing, event streaming, performance optimization, and AI/LLM integrationAI & InnovationLead the delivery of AI-powered features. These include LLM integrations, retrieval-augmented generation (RAG), agentic workflows, MCP server/client implementations, and authoring of Claude Skills. The goal is to extend agent capabilities for domain-specific use cases.Establish best practices for AI-enabled systems including prompt engineering, evaluation frameworks, model observability, and responsible AI guardrailsQuality & Test EngineeringGuide the design and adoption of test harness frameworks across unit, integration, contract, performance, and end-to-end testing layersEstablish AI/LLM-specific evaluation harnesses for prompt regression, output quality scoring, hallucination detection, and evaluation of agentic and MCP-based workflowsChampion shift-left testing, automated regression suites, and quality gates integrated into CI/CD pipelinesCollaborationWork with Product Management, DevOps, Data Science, QA, and other engineering teams to align technical plans with our goalsPartner with security, compliance, and infrastructure teams to ensure platform meets standardsDelivery & ExecutionManage the delivery lifecycle of major platform plansTrack important performance metrics and ensure continuous improvementManage the delivery of insightful dashboards and data visualizationsBachelor's degree in Computer Science, Engineering, or related field8+ years of software engineering experience3+ years in engineering leadership rolesExperience managing real-time, high-throughput API platforms in production environmentsYou have hands-on experience delivering AI/ML or GenAI projects in productionFamiliarity with Model Context Protocol (MCP) and the broader AI tooling ecosystem (e.g., Claude, OpenAI, LangChain, LlamaIndex, or similar agent frameworks)Experience authoring or working with Claude Skills (or analogous capability-extension frameworks) to package domain expertise for AI agentsBackground in test engineering and quality automation, including building or scaling test harness frameworks (e.g., JUnit, pytest, TestNG, Cypress, Playwright, k6, JMeter, and Pact for contract testing)Experience designing evaluation harnesses for AI/LLM systemsKnowledge of distributed systems, cloud platforms (AWS/GCP/Azure), and modern backend stacks (e.g., Node.js, Java, Go, or Python)Experience with API gateways, load balancing, caching, and observability tools (Kibana, Grafana, Datadog, and Prometheus)Familiarity with event-driven architectures, message queues (Kafka) and stream processing frameworksExperience developing ML Ops capabilitiesData Science & ML experienceDevOps Knowledge: Docker and KubernetesOur uniqueness is that we celebrate yours. Experian's culture is people-first, inclusive, and purpose-driven. It is also multi-award-winning. For instance, Fortune named it World's Best Workplaces™ 2025 (Global Top 25) and it earned Great Place To Work™ in 26 countries. Check out Expe