Anti-Abuse Automation Engineer

TL;DR

Anti-Abuse Automation Engineer (Cybersecurity): Building and scaling systems to protect hirify.global's platform from fraud and abuse with an accent on financial fraud, phishing, malware, and platform abuse. Focus on designing detection logic, building automation, and developing workflows to proactively identify and stop bad actors at scale.

Location: If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote.

Salary: The San Francisco, CA base pay range for this role is $170,000 - $280,000. Compensation outside of San Francisco may be adjusted based on employee location.

Company

hirify.global gives developers the tools and cloud infrastructure to build, scale, and secure a faster, more personalized web.

What you will do

• Investigate and proactively identify abuse vectors driving financial loss and platform risk, translating findings into scalable detections.
• Build, iterate on, and operate internal fraud detection tooling, rules, and anomaly alerting systems to enable high-signal, automated enforcement.
• Design and continuously refine operational workflows and automation to scale fraud prevention while reducing manual investigation overhead.
• Partner cross-functionally with Operations, Engineering, Product, and Finance to prioritize risks and ship effective fraud mitigation solutions.
• Act as a key stakeholder in incident response, leading fraud investigations and developing durable mitigation and prevention strategies.

Requirements

• 3+ years in fraud and abuse detection within Trust & Safety, with a strong focus on payment and financial fraud.
• Strong proficiency in SQL and experience navigating large, complex datasets to investigate fraud, generate insights, and build detection logic.
• Designed and implemented automation using scripting and AI tools (LLMs, low/no-code platforms) to streamline investigations and increase enforcement throughput.
• Built and maintained detection logic (rules, heuristics, risk signals), translating investigative insights into scalable, automated workflows.
• Owned the iteration of enforcement and restriction strategies, optimizing for precision, coverage, and loss prevention while minimizing false positives and customer friction.
• Partnered cross-functionally with engineering, data science, and risk teams to productionize detections and integrate ML/LLM capabilities into fraud prevention pipelines.

Nice to have

• Experience detecting and mitigating abuse in developer platforms.
• Familiarity with fraud patterns in cloud infrastructure, SaaS, or edge platforms.
• Experience leveraging signals from network, device, and usage patterns to detect sophisticated abuse.
• Comfort working in fast-moving, product-led environments, rapidly shipping detections and iterating alongside engineering teams.

Culture & Benefits

• Competitive compensation package, including equity.
• Inclusive Healthcare Package.
• Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.
• Flexible Time Off.
• We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.