Senior Staff Software Engineer (Identity & Risk Intelligence)
Build a progressive identity layer
Define how GoFundMe recognizes returning visitors, stitches anonymous device history to a person at signup or login, and raises identity confidence over time, from anonymous visitor to guest to known user.
Architect identity resolution and the identity graph: visitor stitching, account linking, and confidence-weighted models that power personalization, guest donor checkout prefill, and fraud prevention across our consumer and enterprise surfaces.
Build the behavioral signals and identity confidence scoring platform: the data products and APIs that IAM, Integrity, and Payments depend on for real-time trust and authorization decisions.
Shape login risk into adaptive experiences: turn risk signals (bot detection, identity-provider risk events, device intelligence, behavioral signals) into adaptive MFA and step-up authentication that protect against account takeover without adding friction for the legitimate majority.
Shape the login and recognition experience on our CIAM platforms, in partnership with the IAM engineer who anchors them: passwordless authentication, social login, and session decisions informed by recognition and risk, balancing security against funnel conversion across millions of interactions.
Own the platform's approach to large-scale identity-based threats
Bot activity, SMS fraud, credential stuffing, and account manipulation at scale.
This is the emerging cloud security gap that sits between the Auth and Identity and Integrity teams, and closing it is the charter of this role.
Partner with Integrity, Payments, and Decision Science
On identity signal use cases across their distinct needs: account-level trust and T&S feedback loops (Integrity), guest checkout recognition and device fingerprinting (Payments), and bot detection signal quality and experimentation support (Decision Science).
Own the identity and risk intelligence technical roadmap
Priority across product enablement (guest donor experience, identity unification, fraud reduction) and platform durability (signal quality, confidence calibration, model evaluation).