8 months ago
Montréal, CanadaStaff+
Base Salary
$80k - $120k/yr
Responsibilities
- Own the technical vision and architecture for Xsolla’s anti-fraud platform and services.
- Design scalable, resilient systems for real-time transaction risk scoring, rule engines, and decision workflows.
- Lead architecture for Anti-Fraud Systems integrations, internal fraud engines, and third-party providers.
- Translate fraud and risk requirements into technical solutions while meeting performance, reliability, security, and compliance needs.
- Partner with Risk, Payments, Compliance, Product, Data Science, and Operations teams on transaction monitoring, chargebacks, regulatory requirements, and fraud strategies.
- Lead engineers directly or across squads and mentor senior and mid-level engineers.
- Drive code quality, reviews, observability, alerting, secure development, incident response, and root cause analysis.
- Act as the technical escalation point for complex fraud-related incidents and own outcomes in a mission-critical domain.
Requirements
- 8+ years of professional software engineering experience, including significant experience in fintech or payments.
- Proven experience designing or leading Anti-Fraud Systems, including rule engines, risk-scoring pipelines, or decision-orchestration systems.
- Strong backend engineering skills with Java, Kotlin, Go, or similar technologies.
- Experience building high-volume, low-latency distributed systems.
- Understanding of event-driven architecture, APIs and integrations, real-time decisioning data stores, and fraud domain concepts.
- Hands-on experience with payment processing, digital commerce or marketplaces, and preferably gaming or virtual goods.
- Knowledge of fraud patterns, abuse vectors, mitigation techniques, chargebacks, dispute flows, 3DS, risk exemptions, payment scheme rules, and external fraud vendors.
- Ability to lead technically without relying solely on formal authority and make decisions in ambiguous, high-risk domains.
- Strong communication skills for explaining technical and fraud concepts to non-technical stakeholders.
- Preferred: experience with data science or ML-driven fraud models, AML/KYC or regulatory frameworks, global payment platforms or PSPs, and systems operating across multiple regions, currencies, and regulations.
Benefits
- Medical, dental, and vision coverage.
- Paid time off.
- Personalized career roadmap.
- Training and educational opportunities for professional development.
- Support for employees’ physical, mental, and emotional well-being and their families.
