Staff Application Security Engineer

Fingerprint builds device intelligence technology that helps enterprises detect and stop online fraud. The Staff Application Security Engineer will establish and operate the technical foundations of its application security function, including secure development practices, security tooling, vulnerability management, incident response, and engineering enablement.

Responsibilities:

• Design and build Fingerprint's secure development lifecycle: security requirements, threat modeling at design time, secure code review, and pre-release security testing — integrated into how engineers already work, not bolted on as a gate
• Own and operate the security tooling pipeline: SAST, DAST, SCA/dependency scanning, secrets detection, and container/IaC scanning (Snyk and equivalents) — tuned for signal over noise, integrated into CI/CD, with clear ownership and SLAs for findings
• Build the pipeline AI-first: AI-assisted triage and auto-remediation, security review agents that run inside the coding-agent loop and in CI, and AI-augmented testing — and decide, with evidence, what each is trusted to block, flag, or fix on its own
• Build paved-road security: secure defaults, hardened libraries and frameworks, reusable patterns (authn/authz, input validation, secrets handling, crypto) that make the secure path the easy path
• Write code. Contribute fixes, security libraries, CI integrations, and automation directly to engineering repositories
• Lead threat modeling and architecture security reviews for new products, features, and significant changes across the API, SDKs (web and mobile), dashboard, and data pipeline
• Run and mature the vulnerability management program: triage, risk-rate, and drive remediation of findings from scanners, pen tests, bug bounty, and customer reports — with clear severity standards and remediation SLAs
• Partner with the Compliance Lead, who runs the penetration testing program today, on scoping, retesting, and turning findings into engineering work — you bring the technical depth and own remediation
• Perform hands-on security testing of Fingerprint's platform — manual review and exploitation of authn/authz, API, injection, SSRF, business-logic, and abuse-path issues — with particular attention to the fraud and bot-detection threat surface where adversaries actively attempt to defeat the product
• Serve as the technical lead for application-layer security incidents: investigation, containment, root cause, and remediation — partnering with Cloud Platform on infrastructure incidents
• Define what application security logging and alerting should exist, and partner with Cloud Platform and engineering teams to get it built
• Act as the AppSec partner to engineering teams: office hours, design consultations, secure coding guidance, and a Security Champions program that scales your impact beyond one person
• Develop and deliver practical secure coding training grounded in Fingerprint's real codebase and real findings
• Mentor engineers in security thinking and raise the bar through code review and design feedback
• Partner with the Senior Manager, Application Security on the AppSec roadmap: bring technical findings, risk assessments, and recommendations that shape priorities; own execution of the technical program
• Provide the engineering evidence behind security controls when compliance needs it — you make the controls real; the compliance program is owned elsewhere
• Support enterprise customer security conversations with technical depth: questionnaires, architecture questions, pen test summaries, and due diligence calls with customer InfoSec teams
• Contribute to vendor security assessments where third-party code or integrations touch the platform

Requirements:

• 8+ years in software engineering and/or security engineering, with 5+ years focused on application security — you've been the hands-on AppSec engineer at a product company, not a consultant or auditor passing through
• Strong software engineering foundation: You write production-quality code (TypeScript/JavaScript, Go, Python, or similar), understand modern web and API architectures, and are comfortable working inside engineering repositories and CI/CD pipelines
• Deep practical AppSec expertise: OWASP Top 10 and beyond — authentication and authorization design, API security, injection classes, SSRF, cryptography misuse, business-logic and abuse flaws. You can find these issues by hand, explain why they matter, and propose fixes engineers accept
• Threat modeling and security review experience: You've led design-time security reviews for complex systems and produced threat models that engineers used
• Security tooling program experience: You've deployed and tuned SAST/DAST/SCA/secrets-detection tooling in CI/CD and made it useful rather than noisy
• AI-native security tooling: You've run AI-assisted code analysis, triage, or auto-remediation in a real program — not a trial — and have earned opinions about where it's trustworthy, where it generates noise, and what should be allowed to block a merge. You use AI agents daily in your own security work
• Vulnerability management ownership: You've run triage, severity rating, remediation tracking, and pen-test programs with real SLAs
• Influence without authority: A track record of raising security outcomes across engineering teams through credibility, partnership, and good tooling — not mandates
• Clear communication: You write precise findings and design feedback, and you can explain technical risk to engineers, leadership, and customer security teams alike
• Experience in fraud detection, bot mitigation, identity, or device intelligence — the adversarial threat surface here is real and domain-specific
• Cloud security depth on AWS (IAM, network boundaries, secrets management, workload identity) and familiarity with Wiz or equivalent CSPM tooling
• Client-side and mobile SDK security: browser security model, anti-tampering, obfuscation trade-offs, iOS/Android SDK hardening
• Multi-tenant SaaS experience with high-volume, latency-sensitive APIs
• Bug bounty program operation (HackerOne, Bugcrowd, or equivalent)
• AI/ML security awareness: LLM-integrated features, prompt injection, agent tool permissions, model and data-pipeline risks
• Experience with autonomous or AI-augmented penetration testing and attack simulation, and a view on how it complements human-led testing
• Security certifications (OSCP, OSWE, GWAPT, CSSLP) or published research, CVEs, or open-source security contributions
• Experience supporting SOC 2 / ISO 27001 controls as the engineering owner of the control, not the program owner