Infrastructure Engineer

As an Infrastructure Engineer at Zeromatter, you'll design and own the core distributed systems that power our simulation platform. This includes building backend systems and cloud infrastructure that operate reliably under large-scale, compute-intensive workloads.

You will work across services, clusters, and cloud environments to architect systems that handle high concurrency, large data volumes, and complex scheduling. This role is focused on solving hard systems problems across distributed computing, performance, and reliability.

Responsibilities

• Design and own distributed systems that span services, clusters, and cloud environments.

• Architect backend systems and infrastructure for high-concurrency, high-throughput workloads.

• Build systems for scheduling, coordination, and execution of large-scale simulation workloads.

• Design data flows and storage systems for large-scale, latency-sensitive workloads.

• Drive system architecture decisions across backend and infrastructure layers.

• Identify and resolve bottlenecks in distributed systems, including networking, storage, and compute.

• Design fault-tolerant systems with clear failure modes and recovery strategies.

• Build and operate infrastructure across multiple cloud providers and deployment environments.

• Define and implement observability strategies for complex distributed systems.

• Collaborate with engineering teams to ensure systems are scalable, efficient, and maintainable.

Qualifications

• Bachelor's degree in a relevant field (e.g. computer science) or equivalent practical experience.

• Deep experience designing and operating distributed systems in production.

• Strong understanding of system design fundamentals, including concurrency, consistency, and fault tolerance.

• Experience building backend systems in a systems language (Rust, Go, C++, or similar).

• Deep knowledge of cloud infrastructure and distributed computing environments.

• Experience with Kubernetes or similar orchestration systems at scale.

• Strong understanding of networking, storage systems, and performance optimization.

• Experience debugging and operating complex systems under production load.

• Experience with observability and debugging tools for distributed systems.

• Bonus: Experience with large-scale data pipelines or data-intensive systems.

• Bonus: Experience with GPU workloads or high-performance computing.

• Bonus: Experience designing multi-cloud or hybrid cloud systems.