Backend Engineer

Description nSure.ai is the payment fraud prevention provider of choice for Crypto, Gaming and Gift Cards. We offer a managed service based on adaptive AI that deploys, for each customer, a dedicated model trained on their data. Focusing on behavioral patterns - the most accurate and uniquely effective way to mitigate modern scalable fraud - our solution takes a fundamentally different approach to detecting fraud and preventing it from happening. Our customers benefit from the highest-efficacy decisions delivered in under 500 ms, with up to 98% approval rates and a chargeback guarantee, generating zero-risk net incremental profit. We’re looking for a Backend Engineer to join our core team and push forward the technology that powers our fraud prevention engine. In this role, you’ll work closely with Data Analysts and Data Scientists to evolve the logic, infrastructure, and performance of our decision-making systems. You’ll design and build high-performance backend services, improve latency and reliability at scale, and contribute to the architecture of a distributed microservices ecosystem running in Kubernetes. This is an opportunity to make a direct impact on our product, performance, and customers in a fast-moving startup environment where ownership, initiative, and curiosity truly matter. Requirements What We’re Looking For BSc in Computer Science, Software Engineering, or a related field, or equivalent practical experience. 4+ years of backend engineering experience 2+ years of hands-on Node.js experience (TypeScript) Experience with at least one NoSQL document store (e.g., MongoDB, Couchbase) Experience designing and implementing RESTful APIs Experience working with at least one cloud platform (AWS, GCP, or Azure) Strong testing mindset and experience with automated testing frameworks A proactive, curious, and problem-solving mindset with a strong sense of ownership Fluent English (written & spoken) Nice to Have Hands-on experience with at least one streaming or message/event system (Kafka, RabbitMQ, AWS SQS, etc.)] Practical experience with DevOps tooling such as Kubernetes, Helm, Terraform, or other infrastructure-as-code solutions Familiarity with Python Familiarity with ML fundamentals (classification, precision/recall, train/test, etc.) Background in payments, fintech, or fraud prevention Responsibilities Design, develop, and optimize backend services in a modern microservices architecture Build and maintain low-latency APIs that power real-time decisioning Own services end-to-end: deployment, monitoring, scalability, and performance in a Kubernetes environment Improve system reliability, scalability, and security through engineering best practices Write clean, maintainable, and well-tested code (unit + integration tests) Collaborate in architecture discussions, influence decisions, and drive technical improvements