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# Infrastructure Engineer

- **Company:** Recruiting from Scratch
- **Location:** New York, NY, United States (Remote available)
- **Salary:** $130,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Computer Programming, Continuous Delivery, Continuous Integration, Disaster Recovery, Distributed Systems, Github, Python (Programming Language), Data Logging, System Availability, Reliability of Systems, Kubernetes, Infrastructure Automation Frameworks, Deployment Automation, Terraform, Docker
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/infrastructure-engineer-san-francisco-ca--b42500a6-27bd-4bff-823c-c804a59848d3

## About the Role

Funding, Artificial Intelligence (AI), High Availability, Cloud Computing, Systems Reliability, GitHub, Continuous Deployment/Delivery, Continuous Integration, Disaster Recovery, Architectural Design, * Strong experience with cloud platforms (AWS preferred).

 * Proficiency with Infrastructure-as-Code tools (Terraform).
 * Deep experience with containers and orchestration (Docker, Kubernetes).
 * Solid understanding of distributed architectures.
 * Programming experience with Python or Go.
 * Proven ability to ship and maintain reliable infrastructure in production environments.
 * Growth mindset and eagerness to thrive in a hyper-growth, high-ownership environment.

## Description

As an Infrastructure Engineer, you'll build and scale the core systems that support rapid growth, ensuring high availability, cost efficiency, and performance. You will:

 * Design and maintain infrastructure across cloud environments.
 * Build Infrastructure-as-Code workflows to automate deployments and scaling.
 * Improve monitoring, logging, and alerting systems to ensure system reliability.
 * Manage CI/CD pipelines (e.g., GitHub, Spacelift) for seamless deployments.
 * Support disaster recovery planning and high availability strategies.
 * Collaborate with product and research teams to design architectures that scale with workload demands.
 * Identify and resolve performance bottlenecks across compute, storage, and networking., * Impact: Your work directly supports the infrastructure powering the world's leading AI labs.
 * Learning: Gain early insights into frontier model capabilities months before they reach the market.
 * Growth: Work on both infrastructure and research-adjacent projects with rapid paths to ownership.