Job Description

What You Will Do

• Lead the design and development of robust high-performance, cloud-native backend systems using  Go that support real-time data processing and low-latency workflows.
• Drive engineering excellence through code quality, best practices, and mentorship of other team members.
• Work closely with trading, product, and infrastructure teams to understand system requirements and deliver performant solutions.
• Take ownership of production services, ensuring reliability, observability, and performance tuning. Optimize systems performance and ensure system stability, reliability, and security.
• Contribute to infrastructure automation and CI/CD improvements to support rapid deployment and operational agility.
• Conduct in-depth code reviews, lead technical discussions, and influence engineering culture and standards.
• Implement automated testing, CI/CD pipelines, and participate in code reviews and design discussions.
• Deploy and manage services leveraging cloud-native tools and best practices
• Monitor, debug, and troubleshoot production systems and be a part of the on-call incident response team in a high-uptime environment

What You Will Need

• 5+ years of backend development experience, including 3+ years with  Go in production-grade systems.
• Experience leading large-scale system design and mentoring engineers on engineering best practices.
• Strong knowledge of concurrency, memory management, and performance optimization in Go.
• Proven track record of designing and deploying  microservice architectures in high-availability, high-throughput environments.
• Solid understanding of  message queues,  event-driven architectures, and  asynchronous processing
• Strong understanding of  microservice architecture and  REST/gRPC APIs
• Strong understanding of networking data transmission protocols (TCP, UDP, WSS, etc.)
• Experience building and deploying cloud-native applications
• Familiarity with containerization technologies (Docker) and orchestration engines (e.g., ECS, Kubernetes).
• Proficiency with message brokers (e.g., Kafka) and distributed systems.
• Knowledge of data storage technologies such as  PostgreSQL,  Redis, and  time-series databases