Senior Engineering Manager

Who you are

• 8+ years of infrastructure or platform engineering experience, with at least 4 years managing or leading engineering teams at a high-growth technology company
• Fundamentally changed how your team operates because of AI, and you can name the system you designed, the work it absorbed, and what your engineers stopped doing as a result
• Make decisions and move: you set a technical direction with incomplete information, ship something, and adjust based on what the data tells you
• Managed managers or tech leads before, and scaled a team through a period of real growth without letting the performance bar or the culture slip
• Deep hands-on expertise across AWS, Kubernetes, Terraform, ArgoCD, and modern observability tooling, with the ability to debug a complex distributed system yourself when it matters
• Strong business acumen: you treat cloud spend, developer velocity, and reliability as part of enablement and not a cost center. We believe this function to be directly connected business levers rather than separate engineering metrics
• Track record of developing engineers, and you can point to specifically what they went on to do

What the job involves

• You will lead our Compute, Data, and DevEx teams - everything Genius AI ships is powered by what this role owns. You will set the reliability bar, own vendor spend, and build the self-service platform that lets product engineers ship. You will define what the platform becomes and grow/evolve the team who builds it
• You will report to the VP of Engineering. You must be commutable to our San Francisco office and will operate in an in-person environment, as we default to being in-office 3-4 days per week
• Own the technical roadmap for infrastructure and the data platform, defining how we scale from today's footprint to supporting an order of magnitude more traffic while holding a 99.95% uptime target and keeping cloud spend under control across multiple AWS regions
• Continue to shape agentic production operations as the default, building the AI enablement layer that lets engineers delegate routine operational work to agents and reserve their own judgment for novel tasks
• Define the reliability engineering practice with product engineering, standing up SLI and SLO frameworks, managing incident response, and post-mortems
• Raise developer experience across the org through CI platform standardization and self-service tooling that enables teams to manage their own infrastructure as code without a platform engineer in the loop
• Drive incident command during critical outages, then convert every one into a systemic fix instead of a follow-up ticket that ages out
• Own vendor strategy and infrastructure budget, negotiating enterprise contracts and leading migrations to new vendors when the cost or capability case is clear