Software Engineer (Distributed Systems) - Part-Time

Role Overview

We are seeking an elite backend engineer to design and build highly scalable, low-latency distributed systems that serve mission-critical workloads. This role demands deep expertise in microservices architecture, high-concurrency systems, and performance optimization at scale.

You will lead architecture decisions, drive engineering excellence, and build systems that handle millions of requests with strict SLAs, while mentoring engineers and elevating overall team capability.

Core Responsibilities

• Architect and build distributed, fault-tolerant backend systems using modern microservices patterns
• Design and implement high-concurrency APIs with strict latency and throughput constraints
• Own end-to-end system performance, including database, caching, and service-level optimization
• Drive event-driven architectures using Kafka or similar streaming technologies
• Design scalable database solutions (sharding, partitioning, indexing strategies) for large datasets
• Build and optimize CI/CD pipelines and production deployment workflows in cloud environments
• Lead system refactoring and decoupling initiatives in complex legacy environments
• Diagnose and resolve deep production issues under real-world traffic conditions
• Establish and enforce engineering best practices, code quality, and design standards
• Mentor engineers and contribute to a high-performance engineering culture

Specialized Skill Set

Distributed Systems & Architecture

• Proven experience designing large-scale distributed systems handling high QPS (10k+ or more)
• Deep understanding of CAP theorem, consistency models, and fault tolerance
• Hands-on experience with microservices decomposition and service orchestration

Backend & Concurrency

• Advanced proficiency in Java (Spring Boot) for high-performance backend systems
• Strong working knowledge of Go concurrency model (goroutines, channels, GMP scheduling)
• Experience designing systems for high concurrency, low latency, and high availability

Data Layer Expertise

• Expert-level knowledge of MySQL internals (query planner, indexing, sharding strategies, replication)
• Experience managing large-scale datasets (100M+ rows) with performance tuning
• Strong knowledge of Redis caching strategies (cache-aside, write-through, distributed caching pitfalls)

Streaming & Event-Driven Systems

• Hands-on experience with Kafka (consumer groups, partitioning, offset handling, back-pressure)
• Familiarity with event sourcing or asynchronous processing architectures

Cloud & Infrastructure

• Experience designing systems on AWS (Lambda, API Gateway, SQS, or equivalent cloud services)
• Strong Linux expertise: performance tuning, debugging, and shell-level diagnostics
• Experience with observability tools (logs, metrics, tracing)

System Optimization

• Proven ability to identify and eliminate performance bottlenecks across full stack
• Experience tuning systems for sub-100ms latency under load
• Strong debugging skills in production environments under pressure

Preferred Qualifications

• Experience scaling systems to millions of users or requests per day
• Background in high-growth or high-traffic environments
• Exposure to big data ecosystems (Hadoop, Hive)
• Strong ownership mindset with ability to deliver complex systems independently

What Defines a Top Candidate (Behavioral Traits)

• Thinks in systems, not features
• Can predict bottlenecks before they occur
• Makes data-driven architectural decisions
• Balances theoretical knowledge with production pragmatism
• Elevates entire team productivity, not just individual output