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About the Role

As our Staff Infrastructure Engineer, you'll be a key designer and builder of our software factory, which standardizes, automates, and deploys software. This role involves overseeing how we build, verify, deploy, and operate software, with AI accelerating these processes. You will also manage our internal agentic SRE product, supporting the rest of the engineering team. This is a hands-on, staff-level individual contributor position on the Infrastructure team, treating CI pipelines, deploy tooling, and alerting as products with engineering as customers. Success will be measured by increased shipping speed and safety for all teams. You will report to the VP of Engineering and must be commutable to our San Francisco office for in-person work, typically 3-4 days per week with mandatory Tuesdays and Thursdays.

Responsibilities

Scale our CI platform as our orchestration layer for our software factory.
Build systems that let engineers stop worrying about deploys.
Design guardrails, validation, and auto-approval paths for safe infrastructure as code changes by product engineers.
Shape tools, skills, and breakglass access for engineers and AI agents to investigate and resolve incidents across all layers without Infra intervention.
Own SLOs, codify monitoring in Terraform, and eliminate noisy or muted alerts.
Write technical designs, review complex changes, and mentor engineers.
Set the technical direction for the platform for the next few years.

Requirements

8+ years of professional software engineering experience, including several years focused on infrastructure, platform, or developer experience.
A track record of staff-level ownership, setting technical direction for a platform or build/deploy system with 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, including pipeline standardization, self-hosted runners, build caching, progressive delivery, and safe rollbacks.
Strong observability and reliability instincts, including defining SLOs, cleaning up alerting, and implementing system fixes from incident follow-ups.
A product mindset toward internal tooling, measuring success by adoption and reduced need for Infra assistance.
Experience integrating AI tooling into development workflows meaningfully, with opinions on agent roles in build, deploy, and operations.
Experience at a high-growth startup or a small, high-leverage platform team with rapid shipping and ambiguity navigation without heavy process.

Skills

Infrastructure as Code (Terraform)
GitOps (ArgoCD or similar)
CI/CD at scale
Observability
Reliability engineering
Kubernetes
AWS

Location

San Francisco

Work Type

In-person
Hybrid

Experience Level

Staff-level

About the Company

Genius AI is building technology to help local businesses run themselves by automating administrative tasks.
Genius AI products handle tasks like booking, marketing, client management, finances, and staff/inventory management.
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.

Equal Opportunity

Genius AI celebrates differences and is committed to creating a supportive and empowering workplace.
Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer.