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Senior Engineering Manager, Infrastructure

GlossGenius

San Francisco, CA · HybridJob$230–280K/yrPosted 1mo agoStill listed 2 days ago

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At a glance

Compensation
$230–280K/yr
Location
San Francisco, CAHybrid
Work Authorization
Not specified

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Job overview

Genius AI is seeking a Senior Engineering Manager to lead Compute, Data, and DevEx teams, setting reliability standards, managing vendor spend, and building self‑service platforms that enable product engineers to ship efficiently. The role reports to the VP of Engineering and requires in‑person work in the San Francisco office several days a week.

Skills & qualifications

RequiredNice to have

Skills

Developer ExperienceMarketingAmazon Web ServicesInfrastructureEnablementObservabilityDistributed SystemsKubernetesTerraformInventory ManagementData InfrastructureArtificial IntelligenceContinuous IntegrationServiceArgoCDObservability Tooling

Qualifications

8+ Years Infrastructure or Platform Engineering ExperienceAt Least 4 Years Managing or Leading Engineering TeamsManaged Managers or Tech LeadsFundamentally Changed Team Operations Through AIStrong Business AcumenTrack Record of Developing Engineers

Benefits

Medical Insurance
Dental Insurance
Paid Time Off
401(k) Match
Parental Leave
Tuition Assistance

Full job description

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 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. What You'll Do

  • 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

What We're Looking For

  • 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

Benefits & Perks Competitive health & dental insurance options, effective on your first day of employment

  • Flexible PTO

  • In-office lunch twice per week for NYC and SF employees, plus late night dinner stipends

  • Access to Wellhub, a corporate wellness platform with discounted gym memberships, fitness classes, and mental health resources

  • Annual stipend for professional development and continued learning

  • High performers at 5 years receive a $5,000 bonus to use however you recharge best

  • 401k benefit: employees are eligible to contribute starting day 1 of employment

  • Dependent Care FSA

  • Paid parental leave

  • Fertility and adoption benefits via Carrot and Kindbody

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 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.

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