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Lead development of scalable data products for Revenue: design dbt models, metrics, dashboards, governance, and AI enablement. Drive data architecture, quality, lineage, documentation, and automation; mentor analysts and align stakeholders to deliver reliable revenue analytics and reporting.

Build and iterate underwriting ML models for real-time transaction decisions. Develop feature pipelines and training datasets, prototype and evaluate models, productionize into batch or real-time systems, and instrument model/data health, retraining, and monitoring. Collaborate with engineering, risk, product, and ML platform teams to deploy robust, low-latency solutions with appropriate risk controls.

Design and build a next-generation reliability platform for production systems, lead delivery of quarterly goals, collaborate across product/design/analytics, support operations and on-call, set code and design standards, mentor engineers, and integrate AI/LLM-assisted tooling to improve service health and debugging.

Lead and deliver backend batch infrastructure work: own quarterly goals, design and build reliable scalable compute for batch workloads, collaborate with product and stakeholders, run ops/on-call, set code/design standards, mentor engineers, and drive platform reliability and performance.

Build, operate, and extend Affirm's data platform and application tooling to enable self-service data applications at scale. Implement platform features (provisioning, CI/CD, access control), integrations, data governance, automation, observability, and on-call operations. Contribute to roadmap for semantic layers, agentic data tooling, and AI-native workflows while raising engineering and operational standards.

Build and maintain scalable integration and end-to-end test automation frameworks and CI pipelines. Optimize test execution, improve stability and reporting, support engineering teams with triage and best practices, write technical specs/ADRs, participate in on-call rotation, and collaborate across regions to evolve the companys test strategy and developer productivity tooling.

The Senior Product Manager will lead the Customer Servicing team to enhance refunds and disputes platforms, focusing on customer needs and operational efficiencies through AI and automation.

Lead a team of ML engineers to develop and improve fraud detection models, defining strategies and fostering collaboration across functions to ensure effective model integration.

The Senior Staff Software Engineer will lead web platform architecture and development, mentoring engineers while driving improvements in infrastructure, web development strategy, and AI tool integration.

Lead design and delivery of Salesforce architecture and integrations for Revenue. Build custom development (Apex, LWC, Flow), govern CPQ and CLM (Ironclad) solutions, implement Workato integrations, mentor engineers, and partner cross-functionally to scale systems, ensure security, performance, and maintainability, and drive adoption of Salesforce capabilities including Einstein AI.