GlossGenius
Senior Engineering Manager, Infrastructure
San Francisco · Senior
Sponsorship not specified$230k-$280kDetected 67 days ago
Distributed SystemsAWSKubernetesTerraformPlatform EngineeringMachine LearningIncident ResponseInventory ManagementArgo CD
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odds of building a lasting career here
59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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Files H-1B transfers
3 transfer filings in the last year, covering 3 workers. Median labor-condition decision: 819 days. An employer that already files transfers is one that can take over an existing H-1B.
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About the role
- You will report to the VP of Engineering.
Responsibilities
- 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
- 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
- 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
Requirements
- 8+ years of infrastructure or platform engineering experience, with at least 4 years managing or leading engineering teams at a high-growth technology company
- 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
Nice to have
- In-office lunch twice per week for NYC and SF employees, plus late night dinner stipends
Compensation
- Annual stipend for professional development and continued learning
Benefits
- Competitive health & dental insurance options, effective on your first day of employment
- 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
- The base salary for this role is between $230,000-$280,000 + equity + benefits.
- Additionally, this role is currently eligible to participate in Genius AI's equity plan as well as a range of health & wellbeing, retirement savings, and other benefits within our total rewards offering.
- 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.
- The compensation package offered is dependent upon many factors including skills, experience, location, and education.
Company info
- What We're Looking For
- 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
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This listing is sourced directly from GlossGenius's careers page and normalized into a canonical job model.