Software Engineer, Compute Platform

Replit Replit · Enterprise · Foster City, CA · Hybrid · Engineering

Software Engineer role focused on building and enhancing Replit's distributed cloud infrastructure for application deployment, optimizing performance, scalability, and cost-efficiency. Requires strong distributed systems experience and cloud technologies.

What you'd actually do

  1. Expand Replit's cloud infrastructure offerings: Launch new cloud products to be used by Replit Agent to build complex apps. Collaborate with cross-functional teams to design and implement these features, empowering developers with a comprehensive suite of tools to build and deploy their applications efficiently.
  2. Enhance reliability and scalability: Identify bottlenecks, optimize critical paths, and implement robust monitoring and alerting systems. Work closely with the SRE team to ensure high availability and minimal downtime. Enable our customers to seamlessly scale their applications to meet the demands of their growing user base.
  3. Improve utilization of cloud infrastructure: Analyze our infrastructure costs and identify opportunities for optimization. Implement strategies to reduce cloud expenses without compromising performance or reliability. This could involve techniques such as resource provisioning, auto-scaling, cost-aware scheduling, and data lifecycle management. Your efforts will directly contribute to the financial efficiency of our cloud services.

Skills

Required

  • Distributed systems
  • Platform-as-a-service
  • Distributed storage
  • Information retrieval systems
  • Scalable architectures
  • Systems optimization for latency or cost
  • Problem-solving
  • Self-directed and autonomous
  • Versatility and flexibility
  • Continuous learning and adaptability
  • Golang
  • Rust

Nice to have

  • Cloud infrastructure or platform products
  • Application deployment
  • Serverless computing
  • Container orchestration
  • Google Cloud Platform (GCP) services and tools
  • GCE
  • GKE
  • Cloud Run
  • Cloud Storage
  • Contributions to open-source projects

What the JD emphasized

  • distributed systems
  • scalable architectures
  • latency or cost
  • complex challenges
  • Linux internals