This listing pays about $262,500 a year. Across 426 open staff software engineer listings that state pay, the middle half runs $225,000 to $271,000 and the median is $242,500. That is inside the middle half of those listings, 8% above the median.

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Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

About Genius AI

Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more.

Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points.

About the Role

We have committed to a software factory model: a standardized, automated, fault-tolerant path from an idea to production, where humans and AI agents both ship code every day. As our Staff Infrastructure Engineer, you'll be one of the main people designing and building that factory. That covers how we build, verify, deploy and operate software, and how AI accelerates each of those steps. It also includes our own internal agentic SRE product that the rest of engineering leans on. This is a hands-on, staff-level IC role on our Infrastructure team. You will treat CI pipelines, deploy tooling and alerting as products, with the rest of engineering as your customers, and you will judge the work by how much faster and safer every team ships.

You will report to our VP of Engineering. You must be commutable to our San Francisco office and will operate in an in-person environment. We default to being in-office 3-4 days per week with required attendance on Tuesdays and Thursdays.

What You'll Do

- Scale our CI platform as our orchestration layer for our software factory.

- Build systems that let engineers stop worrying about deploys

- Design the guardrails, validation and auto-approval paths that let product engineers change their own infrastructure as code safely, without waiting for an Infra reviewer

- Shape the tools, skills and breakglass access that let engineers and AI agents investigate and resolve incidents across the app, service, compute, storage and network layers, without someone from Infra on the call

- Own SLOs, codify monitoring in Terraform (no more ClickOps), and get rid of noisy or muted-forever monitors across the org

- Write technical designs, review the hard changes and mentor engineers around you. Your judgment will set the direction of the platform for the next few years

What We're Looking For

- 8+ years of professional software engineering experience, including several years focused on infrastructure, platform or developer experience.

- A track record of staff-level ownership: you've set the technical direction for a platform or build/deploy system that many engineers depend on, and you can point to measurable gains in velocity or reliability.

- Deep hands-on experience with a major public cloud (AWS preferred) and operating Kubernetes in production.

- Fluency with infrastructure as code (Terraform) and GitOps-style delivery (ArgoCD or similar).

- Real experience designing CI/CD at scale: pipeline standardization, self-hosted runners, build caching, progressive delivery and safe rollbacks.

- Strong observability and reliability instincts. You've defined SLOs, cleaned up alerting, and turned incident follow-ups into fixes in the system rather than tickets that age out.

- A product mindset toward internal tooling. You measure success by adoption and by how rarely people need to ask Infra for help.

- AI tooling built into your development workflow in a meaningful way. You aren't just aware of the tools; you've changed how you work because of them, and you have opinions on how agents should fit into build, deploy and operations.

- Experience at a high-growth startup or a small, high-leverage platform team where you shipped quickly and worked through ambiguity without heavy process.

At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer.

Personal Information: Notice at Collection for Employees and Applicants https://drive.google.com/file/d/1FF_5dYGdwHfNCMqV4X9NSnCLdnk9z7Ms/view?usp=sharing

Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired.

Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.