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Security Engineer

Stripe · US Remote

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Job description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Abuse Control Engineering (ACE) is Stripe’s rapid-response technical defense and control incubator. When urgent abuse vectors emerge, ACE bridges the gap using real attacker telemetry to prototype, test, and deploy software safeguards before vulnerabilities can be exploited at scale. We partner closely with Fraud, Risk and Product Engineering to run rigorous experiments, balancing aggressive risk mitigation against legitimate user conversion. Operating as both a strike team and an incubator, ACE builds automated regression suites in partnership with Abuse Research to permanently block threat recurrence and seamlessly transfers mature controls to long-term product owners across Stripe.

What you’ll do

As an Abuse Control Engineer on the Abuse Control Engineering (ACE) team, you will design, prototype, and incubate technical defenses that safeguard Stripe’s financial ecosystem against complex, cross-cutting abuse vectors.

Where emerging threat patterns identify Stripe product weaknesses, ACE steps in to rapidly build and experiment with technical safeguards. Driven by empirical evidence and Stripe’s FT3 (Fraud Taxonomy 3.0) framework, you will translate threat intelligence into hard technical control requirements (e.g., API rate-limiting, step-up challenges, parameter validation, pre-debit holds). You will carefully balance security and product velocity, running experiments to evaluate risk reduction against user conversion impact. Managing controls through a strict incubation lifecycle, you will build automated regression suites to prevent recurrence and partner with native product teams to hand off mature, long-term defenses.

Responsibilities

As an Abuse Control Engineer on the Abuse Control Engineering (ACE) team, you will design, prototype, and incubate technical defenses that safeguard Stripe’s financial ecosystem against complex, cross-cutting abuse vectors.

Where emerging threat patterns identify Stripe product weaknesses, ACE steps in to rapidly build and experiment with technical safeguards. Driven by empirical evidence and Stripe’s FT3 (Fraud Taxonomy 3.0) framework, you will translate threat intelligence into hard technical control requirements (e.g., API rate-limiting, step-up challenges, parameter validation, pre-debit holds). You will carefully balance security and product velocity, running experiments to evaluate risk reduction against user conversion impact. Managing controls through a strict incubation lifecycle, you will build automated regression suites to prevent recurrence and partner with native product teams to hand off mature, long-term defenses.

• Rapid Control Prototyping: Design, prototype, and deploy technical controls across API, protocol, and product boundaries to immediately close high-impact abuse vectors. Evidence-Based Technical Requirements: Translate empirical attacker evidence and FT3 threat research Abuse Research, Fraud and Security into precise technical abuse requirements and control specifications.

• Control Co-Design: Collaborate closely with teams across Stripe to co-design resilient, secure controls across payment, onboarding, identity, and Connect surfaces.

• Risk Experimentation: Run rigorous experiments and A/B tests to measure risk reduction against legitimate user conversion impact, optimizing controls to minimize friction while neutralizing threats.

• Regression Testing: Build comprehensive regression testing suites and automated attack simulations with Abuse Research to ensure mitigated abuse vectors do not recur.

• Stakeholder Management: Execute ACE’s incubation model by defining handoff criteria, operational documentation, and target dates to transfer successful controls to product teams.

Requirements

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 3+ years of experience in Security Engineering, Software Engineering, Application Security, or Anti-Abuse Engineering in a high-scale production environment.

• B.S. or M.S. in Computer Science, Cybersecurity, Software Engineering, or a related technical field, or equivalent practical experience.

• Strong software development background with expert proficiency in Python, Go, Java, or similar production languages, alongside expert SQL skills for analyzing system telemetry.

• Hands-on engineering experience building API-level safeguards, rate-limiting frameworks, authentication/authorization checks, or input validation controls.

• Demonstrated 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.

• Proven track record of designing and executing A/B tests, evaluating control efficacy, and balancing security safeguards against user conversion friction.

• Deep expertise in threat modeling, secure system architecture, and modern application security design principles.

• Familiarity with established threat frameworks (e.g., FT3, MITRE ATT&CK) and applying adversary kill chain analysis to build resilient defenses.

• Strong domain knowledge of financial fraud vectors, threat actor TTPs, and attacker infrastructure (e.g., Account Takeover, Card Testing, Credential Stuffing).

• Hands-on experience with large-scale data processing platforms (e.g., Databricks, Trino, PySpark) to monitor and measure control performance across distributed systems.

• Demonstrated capability in incubating software features, establishing clear operational handoff criteria, and seamlessly transitioning ownership to partner engineering teams.

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