Backend Systems Architect

About the Role

Join our core systems team to architect and build ultra-low-latency trading infrastructure and distributed AI systems. You will work with Rust, Go, and C++ to push the boundaries of performance, designing systems that process millions of transactions per second with microsecond-level precision. This role is perfect for engineers who obsess over nanoseconds and love solving complex distributed systems challenges.

Responsibilities

• Design and implement high-throughput, low-latency trading engines capable of processing 10M+ orders per second.
• Build distributed systems for AI model inference and training using cutting-edge frameworks and custom optimizations.
• Architect and optimize database schemas, indexing strategies, and query patterns for sub-millisecond response times.
• Develop custom network protocols and optimize TCP/UDP stack configurations for minimal latency.
• Implement comprehensive monitoring, alerting, and observability solutions using Prometheus, Grafana, and distributed tracing.
• Design fault-tolerant systems with automatic failover, circuit breakers, and graceful degradation strategies.
• Ensure system security through implementation of encryption, authentication, and authorization mechanisms.
• Lead technical design reviews and create detailed architecture documentation for complex distributed systems.

Requirements

• Strong proficiency in systems programming languages: Rust, C++, or Go with 5+ years of production experience.
• Proven experience with high-frequency trading, real-time bidding, or other ultra-low-latency systems (sub-millisecond).
• Deep knowledge of distributed consensus algorithms (Raft, Paxos), event sourcing, and CQRS patterns.
• Expertise in cloud-native technologies including Kubernetes, Docker, gRPC, and service mesh architectures.
• Strong understanding of computer architecture, CPU caching, memory hierarchies, and NUMA optimization.
• Experience with message queues (Kafka, RabbitMQ, NATS) and real-time data streaming architectures.
• Proficiency in performance profiling, benchmarking, and optimization using tools like perf, flamegraphs, and custom instrumentation.
• Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.