Distinguished, Software Engineer

Distinguished Engineer For Fraud Technology

As the Distinguished Engineer for Fraud Technology, you will serve as the technical authority across both Engineering, Platform & Tools teams. You'll drive the vision, architecture, and execution of scalable fraud detection systems, integrating model infrastructure, fraud APIs, internal tools, and platforms. This role plays a critical part in enabling a modern fraud ecosystem that is reliable, efficient, and innovation-ready.

Key Responsibilities

Architecture & Engineering Strategy

Define and lead the architecture for fraud detection infrastructure across APIs, backend systems, and platform components.

Design end-to-end technical solutions for fraud surfaces including Sign-in, Sign-up, Returns, Payment Risk, Driver and Seller Risk.

Own architectural evolution for shared services like the Gateway Layers, Customer Identity Graph, Device Fingerprinting, and Risk APIs.

Partner with platform teams to modernize key components such as databases, feature stores, and streaming/batch pipelines.

Platform & Tooling

Lead development and scaling of critical internal tools

Drive enhancements in Rules Engines, Workflow Engines to support hybrid decision logic (rule + ML stack).

Champion ML Ops and model lifecycle tooling to support training, deployment, monitoring, and governance at scale.

Execution Leadership

Work closely with cross-functional pods to ensure timely and technically sound delivery of fraud solutions.

Collaborate with QA and Release Engineering to strengthen production readiness, monitoring, and holiday resilience.

Ensure architectural alignment and technical consistency across fraud initiatives globally.

Mentorship & Thought Leadership

Mentor senior engineers and guide junior team members in technical and architectural decisions.

Lead cross-org technical reviews and serve as a go-to expert on distributed systems and fraud infra.

Advocate for best practices in security, scalability, cloud optimization, and cost efficiency.

Qualifications

12+ years of experience in backend, systems, or platform engineering roles,

Prior experience in fraud, risk, or identity domains is preferred

Expertise in building large-scale, distributed backend systems and APIs.

Strong understanding of real-time data processing, model inference pipelines, and infrastructure at scale.

Proven success designing internal tooling for analyst, operations, or data science use cases.

Experience driving architectural transformation across both application-level and platform-level domains.

Deep knowledge of modern ML platforms, cloud-native services, and enterprise-grade system reliability.

Minimum Qualifications

Option 1: Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 6 years' experience in software engineering or related area. Option 2: 8 years' experience in software engineering or related area.

Preferred Qualifications

Master's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 4 years' experience in software engineering or related area.

We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.

Primary Location

860 W California Avenue, Sunnyvale, CA 94086-0000, United States of America