Genius AI Staff Software Engineer, Infrastructure at Genius AI designs and builds a software factory for automated, fault-tolerant code deployment. The role includes scaling CI platforms, building deploy systems, and owning SLOs and monitoring.
Responsibilities
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.
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
Qualification
A track record of staff-level ownershipAt Genius AIPersonal InformationAgency Submissions
Required
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.
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