Senior Staff Software Engineer (Identity & Risk Intelligence)

GoFundMe•San Francisco, CA

2d•Hybrid

About The Position

GoFundMe is seeking a Senior Staff Software Engineer, Identity & Risk Intelligence to lead the intelligence aspect of their horizontal Identity Platform Engineering layer. This role will define the technical direction for how GoFundMe recognizes, resolves, and trusts individuals on its platform, and will engineer the systems to support this. The core of the role involves building trust through identity, recognizing returning users, fostering confidence, and applying friction only when necessary. This position will manage this capability at a platform scale, covering both consumer and enterprise platforms, including progressive identity, login risk signals, device intelligence, and an identity confidence layer used by various GoFundMe teams for real-time trust decisions. The engineer will report to the Sr. Manager of Identity and Integrity Engineering and will collaborate with stakeholders across the company to develop solutions for identity resolution, the identity graph, and confidence.

Requirements

8+ years of software engineering experience, with significant time at senior, staff, or principal levels working on identity, risk, fraud, or trust and safety platforms.
Track record of designing and shipping identity resolution, identity graph, behavioral signal, or risk scoring systems that other teams depend on in production.
Deep experience with the technical patterns that underlie this domain: device fingerprinting, visitor stitching, account linking, behavioral feature engineering, confidence calibration, and risk model integration.
Deep identity and CIAM platform experience at scale: auth, sessions, passwordless authentication, social login, and the engineering decisions that balance security against conversion.
Fluency with login risk and adaptive authentication, including risk scoring, step-up flows, and device signals, applied to user experience rather than detection alone.
Strong systems thinking about identity as a risk problem: you understand the difference between authenticating a user and being confident in their identity over time, and you are pragmatic about the friction-vs-security tradeoff and unit economics at scale.

Nice To Haves

Background at a fintech, payments, marketplace, social, or trust and safety-forward company where identity, fraud, and risk were treated as a unified platform problem.
CIAM platform experience (Descope, Okta, Auth0, or comparable) including risk-based and adaptive auth models.
Familiarity with device fingerprint and risk vendors (Alloy, Fingerprint.js, ThreatMetrix) as input signals to a risk and identity confidence layer.
Experience with behavioral analytics and ML-adjacent systems, including feature stores, signal pipelines, and model serving infrastructure, even if you are not primarily an ML engineer.
Experience with compliance and regulatory framing around identity signals (KYC, BSA/AML adjacent, GDPR, CCPA), particularly where device or behavioral signals are involved as approved identifiers.
Public contributions, talks, or thought leadership in the identity, risk, fraud, or trust and safety space.

Responsibilities

Build a progressive identity layer that defines 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.
Design the policy decision and information layer (PDP and PIP) that informs IAM's step-up and session enforcement decisions and Integrity's account-level abuse actions.
Own the platform's approach to large-scale identity-based threats: bot activity, SMS fraud, credential stuffing, and account manipulation at scale.
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, prioritizing across product enablement (guest donor experience, identity unification, fraud reduction) and platform durability (signal quality, confidence calibration, model evaluation).