Backend Engineer (SDE - 2)

Responsibilities:

• Design, develop, and own scalable backend services and APIs, from technical design through to deployment and production stability.
• Develop a deep understanding of trade finance workflows and product requirements, and translate them into well-designed backend services and business logic.
• Design RESTful APIs and database schemas, and optimise complex queries for performance and reliability at scale.
• Strengthen the reliability and observability of production systems through instrumentation, monitoring, and timely resolution of live issues.
• Build dependable integrations across internal services and third-party systems, ensuring consistent data flow across the platform.
• Contribute to system design and architectural decisions service boundaries, API contracts, data models, and scalability trade-offs, alongside technical documentation and improvements to engineering standards.
• Lead and mentor a team of engineers, set technical direction, guide day-to-day execution, uphold code review standards, and contribute to technical hiring.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 4-5 years of hands-on backend development in Java and Spring Boot, including experience designing and operating production-grade distributed systems. Familiarity with Python is a plus.
• Strong command of RESTful API design, microservices architecture, and service-oriented design principles.
• Strong system design and distributed systems fundamentals: service decomposition, inter-service communication, resilience patterns such as retries and circuit breakers, and reasoning about scalability, availability, and consistency trade-offs. An Intelligent layer global trade runs on.
• Proficiency in database design and optimisation (SQL and/or NoSQL), caching strategies (Redis or equivalent), and message queues (Kafka, RabbitMQ, or SQS).
• Experience with Git, CI/CD pipelines, containerization (Docker), and cloud deployment on AWS (EC2 S3 RDS, Lambda, or equivalent).
• Solid grounding in engineering practice: unit testing, code review, and technical documentation.
• Strong problem-solving and communication skills, with the ability to work autonomously and collaborate effectively across functions.
• Experience with AI-assisted development tools (Cursor, Claude Code) is preferred; exposure to LLM APIs or AI-assisted automation is a plus.
• Skills: Java, Spring Boot, RESTful APIs, Microservices, System Design and Distributed Systems SQL / NoSQL Redis Kafka / RabbitMQ / SQS Docker and CI/CD, AWS.