Staff Software Engineer, Infrastructure
About The Position
Genius AI is building technology to help local businesses run themselves by automating administrative work. Its products support tasks such as booking, marketing, client management, finances, staff management, and inventory management. This hands-on, staff-level individual contributor role is on the Infrastructure team and focuses on designing and building Genius AI’s software factory: a standardized, automated, fault-tolerant path from idea to production. The role spans how software is built, verified, deployed, and operated, including how AI can accelerate those activities and the company’s internal agentic SRE product. CI pipelines, deployment tooling, and alerting are treated as products for the rest of engineering, with success measured by how much faster and more safely teams can ship. The position reports to the VP of Engineering. The employee must be commutable to the San Francisco office and work in an in-person environment, with an expectation of being in the office three to four days per week and required attendance on Tuesdays and Thursdays.
Requirements
- At least 8 years of professional software engineering experience, including several years focused on infrastructure, platform, or developer experience.
- Staff-level ownership experience setting the technical direction for a platform or build/deploy system used by many engineers, with measurable gains in velocity or reliability.
- Deep hands-on experience with a major public cloud; AWS is preferred.
- Experience operating Kubernetes in production.
- Fluency with infrastructure as code, particularly Terraform, and GitOps-style delivery such as ArgoCD or similar.
- Experience designing CI/CD at scale, including pipeline standardization, self-hosted runners, build caching, progressive delivery, and safe rollbacks.
- Strong observability and reliability skills, including defining SLOs, improving alerting, and turning incident follow-ups into system fixes.
- A product mindset toward internal tooling, measuring success through adoption and reduced dependence on Infrastructure for help.
- Meaningful use of AI tooling in the development workflow, with informed views on how agents should fit into build, deploy, and operations.
- Experience at a high-growth startup or on a small, high-leverage platform team, shipping quickly and working through ambiguity without heavy process.
Nice To Haves
- Experience with AWS.
- Experience with ArgoCD or a similar GitOps-style delivery tool.
Responsibilities
- Scale the CI platform as the orchestration layer for the software factory.
- Build systems that reduce the need for engineers to worry about deployments.
- Design guardrails, validation, and auto-approval paths so product engineers can safely change infrastructure as code without waiting for an Infrastructure reviewer.
- Shape tools, skills, and breakglass access so engineers and AI agents can investigate and resolve incidents across application, service, compute, storage, and network layers without requiring Infrastructure staff on the call.
- Own SLOs and codify monitoring in Terraform, replacing ClickOps.
- Reduce noisy alerts and monitors that have been muted indefinitely across the organization.
- Write technical designs, review complex changes, and mentor other engineers.
- Set the technical direction of the platform.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
