Sr DevOps Engineer

present of AI; San Francisco (CA); On-site; USD 180,000 - 270,000; Full time

Job summary

Artos in San Francisco is seeking a Senior Infrastructure Engineer to run and scale our cloud platform supporting a life sciences writing product. You will own production operations, incident response, and automation across AWS, Kubernetes, Docker and Terraform.

The role emphasizes reliable, simple designs and infrastructure as code, with collaboration across platform, security, and development teams. Experience with regulated environments and SOC 2 is a plus as we build compute heavy and

Qualifications

• Several years of production operations experience.
• Comfort with infrastructure as code and automation.
• Experience with incident response and on-call rotate.
• Ability to design reliable, simple and scalable infrastructure.

Responsibilities

• Run and scale cloud infrastructure for the platform.
• Troubleshoot incidents and drive incident response.
• Improve developer workflows and deployment pipelines.
• Design patterns that reduce complexity and increase reliability.

Skills

AWS

Kubernetes

Docker

Terraform

Automation

Observability

Tools

AWS

Kubernetes

Docker

Terraform

Job description

Engineering · San Francisco · FullTime · Senior level

The role centers on running and scaling cloud infrastructure for a life sciences writing platform, with heavy hands on work across AWS, Kubernetes, and deployment pipelines. A strong candidate brings several years of production operations experience, comfort with infrastructure as code and automation, and a habit of making systems reliable and simple rather than complex. Troubleshooting incidents and improving developer workflows day to day matter as much as designing new patterns.

How it fits the AI era

Much of the routine work here, from provisioning to pipeline checks to alert triage, is the kind of thing automation and AI assistants increasingly handle, so the job leans toward designing those systems and judging their output. What stays human is architectural judgment, incident response under pressure, and deciding which tools fit the problem without adding needless complexity. The platform itself serves generative AI document work, so infrastructure must support compute heavy and regulated workloads.

How it builds AI experience

This role offers exposure to AI and ML infrastructure, data pipelines, and compute intensive workloads, which the posting lists as a plus. Building that experience means getting hands on with GPU or heavy compute scheduling, cost and reliability tradeoffs for model serving, and security practices for regulated environments. Familiarity with compliance expectations such as SOC 2 would strengthen a candidate for this kind of platform.

Worth showing

• AWS production infrastructure
• Kubernetes and Docker
• Terraform infrastructure as code
• Observability and incident response

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 Artos

Generative AI regulatory document and medical writing platform for life sciences, per the company.