About the Role
The role involves building and maintaining backend services to identify, analyze, and mitigate fraud and abuse risks. The candidate will work closely with data scientists and security teams to develop scalable solutions that protect users and systems.
Responsibilities
- Design and deploy backend services to detect suspicious behavior
- Collaborate with data science teams to integrate risk models into production systems
- Improve system resilience against evolving abuse patterns
- Monitor and respond to real-time fraud signals
- Develop APIs and internal tools for fraud investigation workflows
- Optimize performance and reliability of security-critical services
- Work with product teams to balance security and user experience
- Implement logging and auditing mechanisms for compliance
- Troubleshoot production issues related to fraud systems
- Contribute to incident response protocols for security events
- Write clean, maintainable, and well-tested code
- Participate in code reviews and system design discussions
- Support on-call rotations for critical systems
- Evaluate new technologies for fraud detection capabilities
- Ensure systems scale with growing transaction volume
- Maintain documentation for fraud-related services
- Assist in defining metrics for abuse detection efficacy
- Integrate third-party risk intelligence sources
- Enforce secure coding practices across services
- Collaborate on cross-team initiatives to harden platform security
Nice to Have
- Experience building fraud prevention systems at scale
- Background in machine learning operations or model deployment
- Familiarity with big data platforms like Spark or Flink
- Knowledge of identity verification systems
- Experience with regulatory compliance in financial services
- Prior work in travel or e-commerce domains
- Contributions to open-source security tools
- Exposure to real-time decision engines
- Understanding of A/B testing in risk systems
- Experience with threat intelligence platforms
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid remote
Team
Part of the engineering team focused on security and platform integrity
What We Value
- Ownership of system design and long-term maintainability
- Collaborative problem-solving with cross-functional teams
- Curiosity and continuous learning in security domains
- Clear communication of technical trade-offs
- Focus on measurable impact in fraud reduction
Technology Stack
- Primary languages: Java, Python
- Cloud infrastructure: AWS
- Data stores: PostgreSQL, DynamoDB, Redis
- Messaging: Kafka, SQS
- Orchestration: Kubernetes
- Monitoring: Datadog, CloudWatch
- CI/CD: Jenkins, GitHub Actions
Available for qualified candidates
