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RecargaPay is seeking a Staff Engineer to lead the Anti-Fraud Engineering team, taking ownership of real-time fraud-decisioning systems that protect millions of users and merchants. This is a high-autonomy, high-impact role at the intersection of backend engineering, risk, and compliance, where technical decisions directly influence loss rates and customer trust.
Key Responsibilities:
- Lead architecture of real-time fraud-decisioning services that score transactions, logins, and account changes within sub-second SLAs.
- Own evolution of the fraud rules engine, including rule versioning, safe rollout (shadow/canary), and build tooling for Risk and Fraud Ops analysts to test hypotheses independently.
- Partner with Data Science to productionize fraud-detection models, building low-latency feature pipelines and serving infrastructure with fresh, auditable model inputs.
- Design event-driven pipelines (Kafka) streaming transaction, device, and behavioral signals across services with strict ordering, idempotency, and exactly-once guarantees.
- Build audit trail and explainability layer behind every fraud decision for reconstruction and defense to regulators, card networks, and dispute teams.
- Mentor engineers across levels, championing best practices in coding, system design, and incident response.
- Solve high-scope, high-complexity technical problems often with incomplete signals and real financial exposure.
- Promote AI-assisted engineering practices within the squad using tooling for code generation, automated refactoring, and technical documentation.
Requirements:
- Academic background in computer science, engineering, or software development.
- Hands-on backend engineering experience with Java, Spring Boot, PostgreSQL, Kafka, and AWS.
- Experience designing or operating real-time decisioning, scoring, or rules-engine systems under strict latency budgets.
- Hands-on experience with fraud, risk, or trust & safety systems (transaction scoring, device fingerprinting, velocity/anomaly detection, chargeback/dispute pipelines).
- Solid understanding of event-driven architectures and streaming data (Kafka), including ordering, idempotency, and exactly-once semantics.
- Knowledge of relational databases, Object-Oriented Programming, and Domain-Driven Design; microservice architecture familiarity is a plus.
- Ability to translate compliance and audit requirements (BACEN, LGPD, PCI-DSS) into resilient, explainable system design.
- Experience conducting code reviews, driving knowledge sharing, and promoting collaborative development.
- Proven ability to design complex distributed applications for high performance, throughput, scalability, and reliability.
- Practical experience applying AI frameworks in development projects.
- Python experience is a plus.
Desired Competencies:
- Strategic thinking and proactive problem-solving to close technical and process gaps before they become losses.
- High autonomy and accountability, capable of leading technical decisions with minimal supervision under financial and regulatory pressure.
- Proven mentorship capabilities fostering growth of junior and mid-level engineers.
- Strong communication skills explaining fraud-engineering trade-offs to technical peers and Risk/Compliance stakeholders.
- Comfort navigating ambiguity as fraud patterns shift constantly.
- Demonstrated influence in shaping engineering practices and elevating team-wide technical standards.
- Alignment with company values: ownership, excellence, adaptability, and innovation.
