Mercor · AI infrastructure
Engineering Manager, Fraud & Compliance
- San Francisco (On‑site), +1 more: New York
- Full-time
- $250,000 - $400,000 / year
AI roleAI EngineerBuilds with LLMs
Still open on Mercor's site · checked just now
- Level
- Lead or manager
- Experience
- 5+ years
- Education
- Bachelor's degree
- Posted
- Visa & relocation
- Mercor offers relocation support for this job
See all jobs with visa or relocation supportIn the job ad:
“Up to $15K relocation bonus”
What you'll do
As written by Mercor · Read the original
Why This Role
We're still early.
Fraud is one of Mercor's most important business challenges. Every day, we process enormous volumes of applications, assessments, identity verifications, and work activity across a global talent network. Protecting that ecosystem requires sophisticated systems that can identify fraudulent behavior, evaluate risk, and make accurate decisions at scale — and the playbooks for doing it on an AI-native expert marketplace don't yet exist.
Fraud is an adversarial problem. The solutions that work today may not work six months from now. You'll lead engineering efforts focused on:
Fraud detection and platform integrity — identity verification, abuse prevention, risk scoring, and the LLM-powered decision engines and evaluation pipelines that catch fraudulent behavior as attackers adapt
Compliance and operational infrastructure — the reliability, scalability, and core foundations that allow Mercor to operate globally and meet the obligations of working with the world's leading AI organizations
You'll be responsible for building systems that sit at the center of the AI ecosystem and protect the trust that makes expert knowledge usable at scale.
Lead and grow a high-performing team of engineers responsible for fraud detection, identity verification, abuse prevention, and platform integrity
Define and execute Mercor's fraud and compliance engineering roadmap in partnership with product, operations, and company leadership
Build systems that generate fraud signals, evaluate risk, make automated decisions, and continuously improve through human review and feedback loops
Drive the development of AI-powered detection systems, including LLM-based decision engines, scoring models, and review workflows
Establish rigorous evaluation frameworks to measure detection performance, confidence calibration, false positive/negative tradeoffs, and business impact
Recruit exceptional engineers and raise the talent bar across the organization
Partner closely with product, operations, and company leadership
Drive engineering excellence, velocity, and operational rigor in an adversarial, fast-moving domain
Requirements
Basic Qualifications
Educational Requirements: Bachelor’s Degree in Computer Science or a related technical degree such as Electrical Engineering, Physics, Mathematics or Statistics
5+ years of backend software engineering experience building and operating production systems at scale
3+ years of engineering management experience leading high-performing software engineering teams
Experience leading teams through periods of significant scale, ambiguity, or rapid change, with clear examples of the impact you've personally driven
Nice-to Have Qualifications
2+ years delivering infrastructure for fraud, trust & safety, risk, identity, payments, abuse prevention, or other adversarial domains
2+ years working with machine learning, AI systems, decision engines, or risk-scoring platforms
Skills
Working languages
English
Salary & benefits
Benefits
Generous equity, vested over 4 years
Up to $15K relocation bonus
$10K housing bonus (if you live within 0.5 miles of the office)
$1,500/month meals stipend
Free Equinox membership
$200/month laundry reimbursement
$200/month personal wellness reimbursement
Health, Dental, and Vision insurance
Company
Last checked . The details above were extracted automatically; the employer's original posting is the authority.