Specialist Solutions Architect, Radar (fraud/risk)

Stripe Stripe · Fintech · United States · 1150 Solutions Architecture

Stripe is seeking a Specialist Solutions Architect for their Radar (Fraud/Risk) team. This role involves acting as a domain expert to advise pre-sales teams, influence product roadmaps, and educate customers on Stripe's fraud and risk management platform. The role requires deep knowledge of the fraud ecosystem, including AI-powered detection, ML model tuning, and holistic business risk, and will involve creating reusable assets and coaching others. The candidate will partner with product and sales teams, serve as a voice of the customer, and help resolve complex technical issues.

What you'd actually do

  1. Act as a Subject Matter Expert on Stripe's Radar product suite to accelerate opportunities globally.
  2. Demonstrate a deep understanding and point of view on trends in the fraud and risk management ecosystem, including AI-powered detection, processor-agnostic architectures, and the shift from payment fraud to holistic business risk (e.g., policy abuse, account takeover, first-party misuse).
  3. 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.
  4. Understand the ecosystem of risk and identity integrations (e.g., device fingerprinting, identity verification, bot mitigation, case management) Stripe must support for our users to be successful.
  5. Define, share, and learn best practices and re-usable assets with the broader GTM organization to enhance the quality and efficiency of the team.

Skills

Required

  • 7+ years of experience in a pre-sales, technical consulting, product, or risk strategy role focused on e-commerce fraud prevention, risk management, or trust & safety.
  • Deep working knowledge of the fraud and risk ecosystem, including payment fraud (CNP), account takeover (ATO), first-party misuse (friendly fraud), and policy/content abuse.
  • Demonstrated knowledge of risk management architectures, including the role of rules engines, machine learning models, and manual review queues in fraud decisioning.
  • Strong knowledge of the signals and data used in fraud detection, such as device/IP data, behavioral biometrics, identity verification, and graph-based analysis.
  • Strong knowledge of software engineering and architecture patterns, with the ability to understand how a wide variety of technologies and systems interact with each other.
  • Exceptional communication, presentation, and interpersonal skills, comfortable explaining complex concepts to both technical and non-technical audiences.
  • Interest in solving open ended business problems with a combination of technology and creative thinking.
  • A proven ability to build strong collaborative working relationships with business partners.
  • Ability to deal effectively with ambiguity and thrive in an unstructured, fast-moving environment.

Nice to have

  • Experience integrating Stripe or other RESTful APIs into web applications.
  • Experience with processor-agnostic fraud solutions and multi-processor payment environments.
  • Experience with risk management for various business models, such as platforms/marketplaces, subscription services

What the JD emphasized

  • AI-powered detection
  • ML model tuning
  • fraud and risk management ecosystem
  • advanced fraud systems

Other signals

  • AI-powered detection
  • ML model tuning
  • fraud and risk management ecosystem
  • advanced fraud systems