Staff Software Engineer - Protect
Leads the technical direction and hands-on development of real-time fraud intelligence systems, including scoring, attributes, APIs, and integrations. Requires 8+ years building scalable backend or distributed systems, strong product judgment, and close collaboration with data science, machine learning, and product teams.
About the job
Responsibilities
- Set the technical direction for real-time systems serving Trust Index scores and fraud attributes.
- Lead ambiguous, multi-quarter initiatives while remaining hands-on with architecture, production code, data investigation, and debugging.
- Learn customer fraud challenges and build solutions that address them.
- Identify opportunities in fraud detection, prototype risky assumptions, and turn validated ideas into reliable production systems.
- Collaborate with data science and machine learning teams.
- Navigate data landscapes, run Jupyter notebooks and Spark jobs, and develop in Tecton to deliver business impact.
- Lead AI-assisted engineering through automation, skills, linters, and code contributions across unfamiliar systems and repositories.
- Raise the technical bar through mentorship, design reviews, and hands-on leadership.
Requirements
- Typically 8+ years of experience building and operating backend or distributed systems at scale.
- Extensive hands-on experience working directly in production codebases.
- Strong product judgment and ability to translate ambiguous customer problems into measurable deliverables.
- Ability to make principled tradeoffs between rapid validation and durable architecture.
Nice-to-haves
- Strong opinions, conviction, and product taste.
- Experience building data or API products.
- Experience in the fraud domain.
- Experience or interest in building agentic systems.
Compensation and Benefits
- Salary range: $207,600–$273,600.
- Equity and/or commission may be provided depending on the position.
- Comprehensive benefits include medical, dental, vision, and 401(k).
Skills
Backend Systems, Distributed Systems, APIs, Data Products, Machine Learning, Jupyter, Spark, Tecton, Fraud Detection, Ai-Assisted Engineering, Linters, Production Debugging
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