Distributed Systems Engineer for AI Infrastructure

Stealth Startup

San Francisco (CA)

On-site

USD 150,000 - 210,000

Full time

2 days ago
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Job summary

Stealth Startup is seeking a Systems Engineer to build reliable, scalable infrastructure for our AI-native software engineering platform. You will work on distributed backend services, storage systems, networking, and performance optimization.

This role is ideal for engineers who enjoy solving low-level systems problems, optimizing performance, and building infrastructure that supports millions of code analysis operations.

Qualifications

  • 4+ years of backend or systems engineering experience.
  • Proficiency in Rust, Go, C++, or Java.
  • Experience building distributed systems and microservices.
  • Linux systems programming and networking fundamentals.
  • Cloud infrastructure experience (AWS preferred).
  • Excellent system design and debugging skills.
  • Proven ownership of production infrastructure.

Responsibilities

  • Design and build high-performance distributed backend systems.
  • Develop scalable APIs and services for AI-powered code intelligence.
  • Optimize latency, concurrency, and resource utilization across production infrastructure.
  • Build reliable storage and data processing pipelines for large code repositories.
  • Improve observability through logging, monitoring, and performance diagnostics.
  • Collaborate with ML Engineers to support model serving and inference infrastructure.
  • Contribute to system architecture, reliability, and security best practices.

Skills

Distributed systems
Rust
Go
C++
Java
Linux
AWS
System design
Debugging
Production ownership

Tools

Kubernetes
Docker

Job description

Stealth Startup is seeking a Systems Engineer to build reliable, scalable infrastructure for our AI-native software engineering platform. You will work on distributed backend services, storage systems, networking, and performance optimization.

This role is ideal for engineers who enjoy solving low-level systems problems, optimizing performance, and building infrastructure that supports millions of code analysis operations.

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