Senior Backend Engineer (Paystack)

About the company
Paystack helps businesses in Africa get paid by anyone anywhere in the world. Since 2015 weve built reliable payments infrastructure trusted by hundreds of thousands of businesses processing a significant share of online transactions across the continent. The Risk and Compliance team sits at the core of that trust building the systems that keep our platform safe compliant and resilient as we scale.

About the role
We are looking for a Senior Software Engineer to design build and operate the core systems that power Risk and this role you will take ownership of critical services such as merchant onboarding and KYC/KYB transaction monitoring fraud detection sanctions and watchlist screening case management and regulatory reporting. You will work closely with product managers engineers infrastructure risk analysts compliance officers and operations teams to build systems that meet regulatory requirements while remaining scalable observable and easy to operate. This role requires strong judgment attention to detail and a high bar for correctness in production systems where false negatives can mean real financial loss and false positives can block legitimate businesses.

• Design build deploy and maintain backend services for core risk and compliance domains including merchant onboarding KYC/KYB transaction monitoring fraud detection screening case management and reporting
• Design and build fraud detection systems including rules engines real-time scoring pipelines and feedback loops that adapt to evolving fraud patterns
• Own the implementation of complex backend features end-to-end from requirements and system design through production rollout and ongoing support
• Build and refine merchant onboarding and KYC/KYB workflows that balance friction conversion and regulatory obligations
• Collaborate with cross-functional teams to translate regulatory and risk-policy requirements into robust auditable system designs
• Make and document architectural decisions that prioritise data integrity auditability and system reliability
• Build and maintain internal tools and APIs used by risk analysts compliance officers and operations teams including case management and investigation tooling
• Write high-quality well-tested code and lead by example through thoughtful code reviews
• Identify and mitigate performance risks data consistency issues and security vulnerabilities
• Improve system observability monitoring alerting and incident response practices
• Mentor and support other engineers through technical guidance and knowledge sharing
• Participate in technical interviews and hiring decisions
• Stay up-to-date with emerging technologies fraud trends and regulatory developments to drive innovation within the team

• 6 years of professional software development experience with deep backend ownership
• Strong expertise in Typescript
• Experience with AWS and containerization (Docker Kubernetes)
• Solid understanding of software architecture design patterns and data structures
• Proven experience with RESTful APIs microservices architecture and distributed systems
• Familiarity with CI/CD pipelines and DevOps practices
• Strong grasp of backend security best practices including access control data protection and audit logging
• Experience building systems where wrong decisions have real consequences fraud risk compliance identity or any high-stakes domain where false positives cost money or block real users.
• AI tools usage

• Bachelors degree in Computer Science Engineering or a related field might be beneficial but not required
• Experience building or operating fraud detection anti-money-laundering (AML) or transaction monitoring systems
• Experience designing merchant or customer onboarding and KYC/KYB flows including integrations with identity verification and document-verification providers
• Familiarity with sanctions screening PEP/watchlist matching and entity-resolution techniques
• Experience building rules engines decisioning platforms or real-time scoring/streaming pipelines (e.g. Kafka Flink or similar)
• Experience working in payments banking lending or other regulated financial services environments
• Exposure to regulatory and compliance frameworks (e.g. CBN guidelines AML/CFT regulations GDPR/NDPR audit trails data retention)
• Knowledge of cybersecurity best practices and compliance requirements (e.g. PCI DSS)
• Experience applying machine learning and data analytics to fraud anomaly detection or risk scoring
• Experience building internal admin tools investigation interfaces or operational dashboards
• Familiarity with graph-based analysis or network analysis for detecting fraud rings and collusion

Benefits

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