Senior Cloud Backend Engineer – Distributed Systems (Golang / AWS)

The Objective We are seeking an uncompromising Senior Cloud Backend Engineer to build, scale, and maintain high-throughput, event-driven microservices powering our enterprise platform.

Tailored for a mid-to-senior engineering benchmark, this role requires a battle-tested developer who writes clean, idiomatic Go, commands distributed system architecture, and operates autonomously. You will be held accountable for high system availability, zero-downtime deployments, and rigid code quality.

Core Responsibilities Microservices Architecture: Design, write, and deploy resilient, high-concurrency REST/gRPC microservices using Golang, taking full ownership from technical specification to production rollout.

Event-Driven Systems: Engineer and optimize asynchronous messaging pipelines using Apache Kafka or RabbitMQ to support high TPS (transactions per second) with sub-second processing requirements. Database & Cache Optimization: Architect scalable relational and NoSQL schemas (PostgreSQL, Redis).

Perform deep query profiling, indexing, connection pooling, and deadlock mitigation. Infrastructure & CI/CD: Containerize services using Docker and manage Kubernetes deployments on AWS. Build automated, zero-downtime CI/CD pipelines and configure proactive alerting (Prometheus, Grafana).

System Resilience & On-Call: Conduct rigorous unit/integration testing, enforce strict code review standards, and participate in rotational 2nd-line production support to resolve system incidents swiftly.

Strict Qualifying Criteria Production Experience: Minimum 5+ years of software development experience, with at least 3+ years writing concurrent, production-grade Golang services in a cloud-native setting.

Distributed Systems Mastery: Proven experience building and debugging distributed microservices architectures handling high load, race conditions, and network failures. Database Expertise: Strong proficiency in PostgreSQL (complex joins, execution plans, partitioning) and Redis caching patterns