Specialist Solutions Architect, Fraud & Risk

In-office expectations Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflo

• Pay and benefits [...] Act as a subject matter expert on Stripe's Radar product suite to accelerate opportunities globally
• Develop expertise with the functional and architectural patterns for deploying advanced fraud systems, including the lifecycle of rule management, ML model tuning, and manual review optimization
• Understand the ecosystem of risk and identity integrations (device fingerprinting, identity verification, bot mitigation, case management) Stripe must support for users to be successful [...]
• Solutions Architect
• Employment type
• Full time

Courses relevant to this posting

Relevance is based on skills and concepts, not a guarantee that you qualify.

Covered skills: AI fundamentals Solutions architecture

Skills to close: None listed

Build the skills for this job

Coming-soon courses matched to this posting: outline, waitlist, and skill path.

1. Mapping AI Capabilities to Risk Profiles

Learn to assess what your AI system can do and identify the failure modes and misuse scenarios that matter most.

2. Structuring Safety Evaluations That Test Real Risks

Design evaluation protocols that go beyond benchmarks to test the specific harms your system could cause.

3. Building Decision Frameworks for Release Readiness

Create structured processes that turn safety evidence into clear deployment decisions with defined thresholds.

4. Implementing Independent Review and Separation of Concerns

Structure review processes that separate shipping incentives from safety judgment and ensure accountability.

5. Deploying with Controls and Monitoring Infrastructure

Learn to ship AI systems with runtime safeguards, usage limits, and observability that extends safety beyond the gate.

6. Responding to Incidents and Feeding Lessons Back

Create incident response protocols that detect failures quickly, contain harm, and improve future gates.

7. Adapting Gates for Agents, APIs, and Evolving Systems

Extend deployment gate frameworks to handle AI agents, third-party integrations, and systems that change post-release.

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