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Join Stripe as an Abuse Research Engineer to proactively hunt for advanced threats and dissect complex fraud vectors, safeguarding Stripe’s financial ecosystem.
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.
Responsibilities
- Proactive Threat Hunting & Kill Chain Analysis: Formulate hypotheses and conduct iterative threat hunting operations across Stripe systems and external data.
- FT3 Taxonomy: Apply and enrich the FT3 framework across empirical datasets and incidents, standardizing threat intelligence across kill chain phases and targeted API endpoints.
- Threat Intelligence & Signal Expansion: Partner with teams like Fraud Intelligence to integrate, curate, and automate threat feeds into engineering workflows.
- Cross-Functional Advisories & Strategic Controls: Translate raw research and retrospective findings into actionable threat advisories and control recommendations (policy, technical systems, support workflows, and detection mechanisms) for stakeholders across Fraud, Risk, Onboarding, and Security.
- Agentic Testing & Adversary Simulation: Utilize agentic automated testing frameworks to simulate adversary TTPs, validate whether deployed controls interrupt empirical kill chains, and generate regression scenarios to exercise controls.
Requirements
- 5+ years of experience conducting threat intelligence, threat hunting, or technical incident response within cyber security, product abuse, or trust domains.
- 5+ years of experience analyzing large, complex datasets using data analytics tools to identify anomalies, map behavioral trends, and solve complex fraud problems.
- B.S. or M.S. in Computer Science, Cybersecurity, or a related technical field, or equivalent practical experience.
- Expert proficiency in Python and SQL, with demonstrated experience using code and scripting to automate workflows, build investigative tools, or query big data pipelines.
- Hands-on experience in log analysis (e.g., application logs, API route telemetry, network security events), digital forensics, and cyber investigation methodologies.
- Strong communication skills with a proven ability to translate complex technical research into clear, actionable recommendations and advisories for cross-functional partners.