Senior Staff Software Engineer (Identity & Risk Intelligence)

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.

• Own 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.

• 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).

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.
• 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.

Skills:

• 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.

Benefits:

• Competitive pay and comprehensive healthcare benefits.
• Financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
• Participation in learning, development, and recognition programs to help you thrive and grow.
• Commitment to DEI through ongoing initiatives and employee resource groups.
• Community engagement through our volunteering program.