Principal Distributed Systems Optimization Engineer

About the role

Job Description

We are seeking a Principal Distributed Systems Optimization Engineer to design, analyze, and optimize large-scale, high-throughput distributed systems. This role focuses on improving system performance, reliability, and cost efficiency across complex service-oriented architectures operating at significant scale.

You will work closely with backend engineers, data infrastructure teams, and platform reliability groups to identify bottlenecks, redesign critical paths, and implement robust, fault-tolerant solutions. The ideal candidate has deep expertise in distributed systems theory and hands-on experience tuning production systems under heavy load.

Key Responsibilities

Analyze system performance using metrics, tracing, and profiling tools to identify latency and throughput bottlenecks

Design and implement optimizations across microservices, data pipelines, and storage layers

Improve system reliability through fault isolation, graceful degradation, and resilience patterns

Lead architectural reviews and propose scalable design improvements

Collaborate with cross-functional teams to drive performance best practices

Build tooling and frameworks for performance benchmarking and capacity planning

Mentor engineers on distributed systems concepts and performance engineering

Required Qualifications

8+ years of experience in backend or distributed systems engineering

Strong understanding of distributed systems concepts (consensus, partitioning, replication, consistency models)

Proficiency in one or more programming languages such as Java, Scala, Go, or Python

Experience with large-scale data systems (e.g., streaming platforms, distributed databases)

Deep knowledge of performance tuning, profiling, and observability tools

Preferred Qualifications

Experience with systems like Kafka, Spark, Flink, or similar technologies

Familiarity with cloud platforms and container orchestration (e.g., Kubernetes)

Background in high-QPS, low-latency systems

Experience designing systems with strict SLAs and SLOs

What You’ll Work On

Optimizing services handling millions of requests per second

Reducing tail latency and improving system predictability

Enhancing observability and debugging capabilities in complex environments

Driving initiatives to reduce infrastructure cost while maintaining performance