Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
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Member of Technical Staff, Infrastructure
- Location
- Sunnyvale
- Type
- Full time
- Posted
- 5MO AGO
About the role
We are looking for highly capable and execution-focused Member of Technical Staff (Infrastructure) to build and scale the core systems powering AI-driven software development. This role requires strong systems thinking, deep infrastructure expertise, and the ability to operate in a fast-paced, ambiguous environment.
Key ResponsibilitiesCore Infrastructure
Design, build, and maintain distributed systems that power our AI platform and developer tools.
Architect and scale high-throughput, low-latency backend services.
Optimize performance, reliability, and cost across the infrastructure stack.
Cloud & Deployment Systems
Operate and improve cloud-native environments (AWS, GCP, or Azure).
Build automation for deployment, provisioning, and environment lifecycle management.
Implement secure, scalable, and repeatable CI/CD pipelines.
AI Infrastructure
Support infrastructure for model inference, training, and evaluation pipelines.
Work closely with AI teams to operationalize models at scale.
Build systems for prompt orchestration, agent execution, and developer tool integration.
Reliability & Observability
Establish observability standards (metrics, logging, tracing).
Drive incident response, debugging, and reliability engineering practices.
Contribute to security, compliance, and data privacy best practices.
Collaboration
Partner across AI, product, and engineering teams to unblock delivery.
Contribute to technical planning, architecture reviews, and infrastructure strategy.
3+ years of experience in backend or infrastructure engineering.
Strong understanding of distributed systems, networking, and cloud architecture.
Proficiency in Go, Python, or Rust.
Experience with Docker, Kubernetes, and infrastructure-as-code tools (Terraform, Pulumi).
Familiarity with CI/CD, observability tools, and cloud-native design patterns.
Ability to operate independently and deliver under ambiguity.
Ownership and accountability across the full infrastructure stack.
Pragmatism over over-engineering.
Speed without compromising reliability.
Curiosity about AI systems and their infrastructure implications.
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