Staff Engineer, Cyber Fraud

Quick Facts

• Role: Staff Engineer, Cyber Fraud

• Focus: Backend engineering leadership for fraud prevention, risk assessment, and real-time detection

Description

You will be the technical anchor for Shipt’s fraud prevention ecosystem, architecting and building scalable risk assessment systems and mission-critical APIs. The role emphasizes low-latency fraud detection, security and scalability, and close collaboration with Data Science to expand in-house rules engines and ML models. You will also drive observability (logging, metrics, alerting), documentation/artifacts, and provide technical mentorship and incident/on-call support.

Responsibilities

• Architect, build, and deploy mission-critical APIs and services with high code quality, security, and scalability

• Create low-latency integrations for real-time fraud and abuse detection and response

• Partner with Data Science on in-house rules engines and ML model expansion

• Produce technical implementation proposals based on research and discovery

• Implement and maintain logging, metrics, and alerting for performance and reliability

• Create and maintain high-fidelity documentation, diagrams, and data models

• Serve as primary subject matter expert for the Cyber Fraud team and collaborate across Engineering, Finance, Legal, and Operations

• Lead architectural design reviews and provide technical mentorship

• Participate in on-call duties: incident response, debugging, and ad-hoc fraud consultation

• Proactively identify and analyze fraud vectors and propose engineering solutions with minimal user impact

• Support AI acceleration and adoption across teams

Requirements

• 8+ years of backend engineering experience

• Expertise in backend languages such as Go, JavaScript, or Python

• Proven API development and integrations experience

• Extensive experience with Git and GitHub

• Strong experience with PostgreSQL and Snowflake for data storage, retrieval, and analysis

• Proven experience integrating with 3rd-party vendors

• Experience with Kafka or AWS SNS/SQS

• Experience with observability tools such as Datadog, Grafana, and Prometheus

• Ability to identify and optimize inefficient code, database queries, and network requests

• Bachelor’s degree or equivalent experience

Benefits

• Medical, dental, vision, and additional coverage for employees and eligible family members

• Eligibility to enroll in a 401(k) plan

• Discretionary vacation for exempt team members, paid holidays, and paid sick leave

• Annual bonus eligibility and potential restricted stock units (RSUs) based on role

• Pay range guideline: $95,800–$185,000 (total compensation varies by qualifications, skills, competencies, and work location)