Backend Architect
CodeRound is hiring for this role.
- Backend Architect
- Backend Engineering
- System Design
- Distributed Systems
- High-Scale Systems
- High QPS
- Low Latency
- Python
- Golang
- Quick Commerce
- Consumer Internet
- Marketplace
- Microservices
- Queues
- Data Modeling
- Database Optimization
- Observability
- Scalability
- Performance Optimization
- Cloud Infrastructure
- Platform Architecture
We are looking for a hands-on Backend Architect to own the architecture, scalability, and performance of a high-traffic consumer platform. The ideal candidate will have deep experience building and scaling distributed backend systems in consumer internet, quick commerce, or marketplace environments. This is an individual contributor role requiring strong system-level ownership, sound architectural judgment, and the ability to solve complex engineering challenges across the platform.
What you'll do
- Own the end-to-end backend architecture, ensuring scalability, reliability, and performance across the platform.
- Design, build, and optimize distributed systems capable of handling high traffic, high QPS, and low-latency requirements.
- Drive system-level technical decisions across service architecture, data models, APIs, and inter-service communication.
- Identify and resolve performance bottlenecks, improve system reliability, and optimize backend infrastructure for scale.
- Design robust asynchronous processing and queue-based workflows to support high-throughput operations.
- Establish best practices for observability, monitoring, logging, tracing, and production incident resolution.
- Lead database architecture and data modeling decisions, focusing on query efficiency, consistency, and scalability.
- Evaluate architectural trade-offs across performance, availability, maintainability, and infrastructure costs.
- Collaborate with the CEO and leadership team on critical technical decisions, platform strategy, and long-term engineering priorities.
- Maintain a hands-on approach by writing code, reviewing implementations, and driving complex engineering problems to resolution.
- Strengthen existing systems to support growing transaction volumes, user traffic, and evolving product requirements.
- Identify opportunities to simplify backend architecture, reduce technical debt, and improve engineering efficiency.
Must have
7+ years of experience in backend engineering, with strong hands-on development experience. Proven experience building and scaling high-traffic consumer internet, quick commerce, or marketplace platforms. Strong understanding of distributed systems, high-QPS architectures, low-latency services, and performance optimization. Experience designing scalable backend architectures with robust queueing systems, asynchronous processing, and reliable service communication. Strong expertise in data modeling, database design, query optimization, and efficient data access patterns. Proficiency in Python preferred; candidates working primarily with Go or other languages are welcome, provided they have familiarity with Python. Experience with production observability, monitoring, logging, tracing, and troubleshooting complex distributed systems. Demonstrated system-level ownership, including architectural decisions, scalability improvements, reliability, and production performance. Strong problem-solving skills and the ability to make pragmatic engineering trade-offs in a high-growth environment.
Good to have
Experience building backend systems from zero to one, including defining architecture and establishing engineering foundations. Experience with high-scale e-commerce, hyperlocal delivery, logistics, or real-time inventory and order management systems. Exposure to cloud infrastructure, containerization, caching, database sharding, and distributed system resilience patterns. Experience optimizing infrastructure costs while maintaining performance, availability, and reliability. Experience working closely with founders and leadership teams on platform strategy and technical decisions. Familiarity with event-driven architectures, stream processing, and large-scale data pipelines.