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SoFi is seeking a Principal Software Engineer to architect and build sophisticated fraud detection and anti-money laundering solutions using cutting-edge technologies and data-driven approaches to protect SoFi's members and business.

Requirements

• Expert-level proficiency in languages suitable for high-performance financial systems.
• Deep experience with Apache Kafka, Apache Flink, and real-time event processing architectures.
• Hands-on experience with AWS SageMaker, Feature Store, and ML model deployment frameworks.
• Expertise in Snowflake, AWS DynamoDB, and time-series databases for fraud analytics.
• Experience with AWS Neptune and Gremlin for relationship analysis and investigation workflows.
• Experience with rule engines like Flowable, Camunda, or similar decisioning platforms.
• Proficiency with Apache Druid or similar OLAP systems for operational analytics.

Responsibilities

• Real-time Fraud Detection: Design and implement advanced fraud detection systems using machine learning models, real-time streaming analytics, and complex event processing.
• AML Compliance Solutions: Build comprehensive anti-money laundering solutions including transaction monitoring, customer due diligence (CDD), and suspicious activity reporting systems.
• Data-Driven Risk Models: Develop sophisticated risk scoring models leveraging Member360 unified data layer and advanced analytics capabilities.
• Streaming Data Architecture: Build real-time data pipelines using Apache Kafka, Apache Flink, and AWS Kinesis for processing high-volume transaction streams.
• Machine Learning Integration: Implement ML models using AWS SageMaker, Feature Store, and the Batch Inference Framework for fraud and AML detection.
• Graph Analytics: Develop entity relationship analysis using AWS Neptune for investigating complex fraud patterns and money laundering networks.
• Real-time Analytics: Build operational dashboards and investigative tools using Apache Druid for seconds-fresh fraud and AML analytics.

Other

• Bachelor's degree with 15+ years of experience, or Master's degree with 12+ years, or PhD with 8+ years
• Extensive experience building fraud detection or AML solutions in financial services
• Proven track record with real-time data processing, machine learning, and high-scale distributed systems.
• Deep understanding of financial crime patterns and regulatory requirements.
• The position is based in Seattle or San Francisco