Infrastructure Engineer

Infrastructure Engineer Base Salary: $150,000–$300,000 + competitive equity Location: New York City or San Francisco Work Arrangement: On-site 5 days per week Visa: Sponsorship and eligible visa transfers available, including H-1B transfers and OPT A fast-growing, $50M Series A AI infrastructure startup backed by Sequoia Capital is hiring Infrastructure Engineers to help build and scale the foundation of its enterprise AI platform. The company is building secure, enterprise-grade AI data infrastructure for financial services. Its founders previously helped scale engineering and AI/ML organizations at Stripe and Notion, and the team is expanding to support significant customer demand. This is an opportunity to join as one of the company's first ~20 engineers and take meaningful ownership of the infrastructure that supports sensitive enterprise and financial data. What you'll do Build and scale secure, production-grade cloud infrastructure across AWS, GCP, and/or AzureDeploy and operate containerized workloads using KubernetesBuild and improve CI/CD pipelines and infrastructure-as-code systemsDevelop infrastructure supporting AI and data-intensive workloadsBuild monitoring, alerting, observability, and production reliability systemsSupport secure enterprise and private-cloud deploymentsBuild infrastructure for complex data ingestion and processing pipelinesImplement access controls, auditability, security, and data-governance practicesImprove infrastructure performance, scalability, reliability, and cost efficiencyHelp shape infrastructure architecture and engineering practices as the company scales What we're looking for 3–10 years of infrastructure, platform, cloud, SRE, or closely related software engineering experience.Hands-on production experience with AWS, GCP, or AzureStrong experience with Kubernetes and containerized infrastructureExperience building or owning production-scale infrastructure, not simply supporting systems designed by othersExperience with CI/CD, infrastructure as code, observability, and production reliabilityStrong software engineering fundamentals and the ability to work beyond configuration and operationsExperience operating secure, reliable systems in productionEvidence of increasing technical scope, ownership, and responsibilityCandidates may come from either a cloud/platform infrastructure background or a data infrastructure background involving complex production ingestion and processing systems. Particularly valuable experience Engineering experience in a high-bar, technically rigorous startup or engineering organizationRapid career progression or unusually broad technical ownershipEarly-stage or high-growth startup experienceTerraformDistributed systemsData ingestion, ETL, or real-time processing infrastructureAI/ML infrastructure, including LLM inference or training infrastructureSecurity, compliance, data governance, or regulated-industry environmentsDatadog, Prometheus, Grafana, or similar observability platformsAWS SageMaker, Bedrock, or related AI infrastructureExperience working across multiple cloud environments