Staff Security Engineer, Abuse Control

at Stripe
EUR 132,000-198,000 per year
SENIOR
✅ On-site

Tech Stack

AI @ 4 API @ 4 Automated Testing @ 4 Communication @ 7 Databricks @ 4 Distributed Systems @ 4 Fraud @ 4 Go @ 7 Java @ 7 Payments Python @ 7 SQL @ 6 Security @ 8 Software Development @ 7 Trino @ 4

Details

About the Team

Abuse Control Engineering (ACE) is Stripe’s rapid-response technical defense and control incubator. When urgent abuse vectors emerge, ACE uses real-world attacker telemetry to prototype, test, and deploy software safeguards before vulnerabilities can be exploited at scale.

ACE partners with Fraud, Risk, Abuse Research, and Product Engineering to run rigorous experiments that balance effective risk mitigation with legitimate user activity and conversion. The team builds automated regression suites to prevent threats from recurring and transfers mature controls to long-term product owners across Stripe.

As an Abuse Control Engineer on the ACE team, you will design, prototype, and incubate technical defenses that safeguard Stripe’s financial ecosystem against complex, cross-cutting abuse vectors. You will translate threat intelligence into precise technical control requirements, such as API rate limits, step-up challenges, parameter validation, and pre-debit holds.

Responsibilities

  • Design, prototype, and deploy technical controls across API, protocol, and product boundaries to address high-impact abuse vectors.
  • Translate empirical attacker evidence and FT3 threat research from Abuse Research, Fraud, and Security teams into precise technical abuse requirements and control specifications.
  • Collaborate with teams across Stripe to design resilient, secure controls across payments, onboarding, identity, and Connect surfaces.
  • Run rigorous experiments and A/B tests to measure risk reduction against the impact on legitimate user conversion, optimizing controls to minimize friction while neutralizing threats.
  • Build comprehensive regression test suites and automated attack simulations with Abuse Research to ensure mitigated abuse vectors do not recur.
  • Execute ACE’s incubation model by defining handoff criteria, operational documentation, timelines, and target dates for transferring successful controls to product teams.

Requirements

  • 10+ years of experience in security engineering, software engineering, application security, or anti-abuse engineering in a high-scale production environment.
  • A bachelor’s or master’s degree in computer science, cybersecurity, software engineering, or a related technical field, or equivalent practical experience.
  • Strong software development background, with proficiency in Python, Go, Java, or a similar production programming language.
  • Advanced SQL skills for analyzing system telemetry.
  • Experience using frontier AI models for software development, learning, and analysis.
  • Hands-on experience building API-level safeguards, rate-limiting frameworks, authentication or authorization checks, or input-validation controls.
  • Experience with automated testing frameworks, including writing unit, integration, and regression tests for critical backend software.
  • Strong cross-functional collaboration and communication skills, with a track record of partnering across security, product, and platform teams to drive technical outcomes.

Preferred Qualifications

  • Experience designing and executing A/B tests, evaluating control efficacy, and balancing security safeguards against user conversion friction.
  • Expertise in threat modeling, secure systems architecture, and modern application-security design principles.
  • Familiarity with threat frameworks such as FT3 or MITRE ATT&CK, and experience applying adversary kill-chain analysis to build resilient defenses.
  • Knowledge of financial fraud vectors, threat-actor tactics, techniques, and procedures, and attacker infrastructure, including account takeover, card testing, and credential stuffing.
  • Hands-on experience with large-scale data-processing platforms such as Databricks, Trino, or PySpark to monitor and measure control performance across distributed systems.
  • Experience incubating software features, establishing clear operational handoff criteria, and transitioning ownership to partner engineering teams.

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