Senior Software Engineer

Design and build reliable signal-collection and feature pipelines for fraud and abuse detection. Design the compute, storage and serving architecture used to build and score large account graphs. Build and operate model deployment, versioning, monitoring, rollback, shadow evaluation and staged-rollout capabilities. Integrate risk decisions with serving and enforcement systems, including audit, review and reinstatement workflows. Build investigation tools that help analysts examine account clusters, review evidence and document decisions. Own the performance, reliability, observability, security and operational health of these systems, working with product and partner engineering teams on production integration. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. These requirements include but are not limited to the following specialized security screenings: Bachelor's Degree in Computer Science or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR Master's Degree in Computer Science or related technical discipline AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR equivalent experience. 2+ years experience building and operating distributed backend services or large-scale data pipelines in a production environment. Experience with graph processing at scale, or with the storage patterns behind entity resolution over large account populations. Background in trust and safety, anti-fraud, or platform abuse systems, including the operational side of enforcement and appeals. Familiarity with Azure services, identity and tenant concepts, or API gateway and rate-limiting infrastructure. Experience integrating with existing internal platforms and data estates, including schemas, data contracts, access controls, retention requirements and upstream service changes.