Infrastructure Engineer

present of AI; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

present of AI is seeking a Platform Engineer focused on building and scaling the infrastructure that runs a fast-growing AI code reviewer product. The role involves hands-on work with containers, Kubernetes, Terraform, Linux VMs, and cloud platforms, plus strong networking knowledge.

You will work directly with customer teams to install and operate the product in self-hosted and air-gapped environments, ensuring reliability, security and performance as usage climbs.

Qualifications

• Hands-on experience with containerized workloads and orchestration.
• Strong knowledge of Kubernetes, Terraform, Linux VMs and cloud platforms.
• Solid networking knowledge and customer-facing patience.

Responsibilities

• Build and scale the systems that keep the product running for a fast-growing user base.
• Assist large customers with installing the product in their own environments.
• Ensure sandboxing and isolation for reliable, secure deployments.

Skills

Containers

Kubernetes

Linux

Networking

Cloud platforms

Tools

Terraform

Kubernetes

Job description

The role is mostly about building and scaling the systems that keep a fast-growing product running, then helping large customers install it inside their own environments. A strong candidate has hands-on time with containers, Kubernetes, Terraform, Linux virtual machines and cloud platforms, plus solid networking knowledge. Patience with customers matters, since part of the job is working directly with their teams.

How it fits the AI era

The product is an AI code reviewer, so much of the work is keeping model-driven workloads reliable, fast and isolated as usage climbs. Open problems like running feature branches and letting agents try to break them depend on safe sandboxes, which is infrastructure work. Judgment about failure modes, customer trust and security in locked-down settings stays with people.

How it builds AI experience

The role offers close exposure to how an AI code review product is deployed, scaled and run, including in self-hosted and air-gapped setups. Someone could build relevant experience by setting up sandboxed environments that run code safely, or by self-hosting an open source model or agent tool on Kubernetes. Following how code indexing and review agents use compute would also help.

Worth showing

• Kubernetes and Terraform projects
• Linux and networking depth

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Greptile

An AI code reviewer that indexes a team's whole codebase as a graph first, so it can catch bugs a diff-only tool would miss.