Tech Lead

Xsolla·Canada·Офис·2 мес. назад

LeadManagement

ABOUT YOU We are looking for a Tech Lead to drive the technical direction, architecture, and delivery of Xsolla’s fraud prevention and risk systems. This role requires deep fintech and payments experience, strong understanding of Anti-Fraud Systems (AFS), and the ability to lead engineers building high-throughput, low-latency, decision-critical systems. You will work closely with Product, Data Science, Risk Operations, Compliance, and Platform teams to design and evolve fraud detection, prevention, and investigation capabilities at global scale. ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com.

Technical Leadership & Architecture

Own the technical vision and architecture of Xsolla’s anti-fraud platform and services.

Design scalable, resilient systems for real-time transaction risk scoring, rule engines, and decision workflows.

Lead architectural decisions around AFS integrations, internal fraud engines, and third-party providers.

Ensure systems meet performance, reliability, security, and compliance requirements.

Fraud & Fintech Domain Leadership

Translate fraud and risk requirements into robust technical solutions.

Partner with Risk, Payments, and Compliance teams on: Transaction monitoring, Chargeback reduction, AML / KYC-adjacent workflows (where applicable), and Regulatory and scheme requirements (Visa, Mastercard, etc.)

Evaluate and evolve fraud strategies across: Card-not-present transactions, Alternative payment methods, Digital goods and gaming-specific fraud vectors

Engineering Execution: Lead a team of engineers (directly or as a technical lead across squads), Drive best practices in: Code quality and reviews, System observability and alerting, Secure development, and Incident response and root cause analysis

Balance speed, risk, and quality in a high-impact domain.

Collaboration & Influence: Work cross-functionally with Product Managers, Data Scientists, and Operations

Mentor senior and mid-level engineers in both technical depth and domain expertise.

Act as a technical escalation point for complex fraud-related incidents.

8+ years of professional software engineering experience, with significant time in fintech or payments.

Proven experience designing or leading Anti-Fraud Systems (AFS), such as: Rule engines, Risk scoring pipelines, and Decision orchestration systems

Strong backend engineering skills (e.g., Java, Kotlin, Go, or similar).

Experience building high-volume, low-latency distributed systems.

Deep understanding of Event-driven architecture, APIs and integrations, Data stores used for real-time decisioning, and Domain Expertise

Hands-on experience with fraud prevention in: Payment processing, Digital commerce or marketplaces, and Gaming or virtual goods (strong plus)

Understanding of fraud patterns, abuse vectors, and mitigation techniques.

Familiarity with: Chargebacks and dispute flows, 3DS, risk exemptions, and payment scheme rules, and Working with external fraud vendors and tools

Proven ability to lead technically without relying solely on formal authority.

Strong decision-making skills in ambiguous, high-risk domains.

Excellent communication skills, able to explain complex technical and fraud concepts to non-technical stakeholders.

Comfortable owning outcomes in a mission-critical area.

Experience working with data science or ML-driven fraud models.

Knowledge of AML, KYC, or regulatory frameworks.