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 Azure
• Deploy and operate containerized workloads using Kubernetes
• Build and improve CI/CD pipelines and infrastructure-as-code systems
• Develop infrastructure supporting AI and data-intensive workloads
• Build monitoring, alerting, observability, and production reliability systems
• Support secure enterprise and private-cloud deployments
• Build infrastructure for complex data ingestion and processing pipelines
• Implement access controls, auditability, security, and data-governance practices
• Improve infrastructure performance, scalability, reliability, and cost efficiency
• Help 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 Azure
• Strong experience with Kubernetes and containerized infrastructure
• Experience building or owning production-scale infrastructure, not simply supporting systems designed by others
• Experience with CI/CD, infrastructure as code, observability, and production reliability
• Strong software engineering fundamentals and the ability to work beyond configuration and operations
• Experience operating secure, reliable systems in production
• Evidence of increasing technical scope, ownership, and responsibility
• Candidates 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 organization
• Rapid career progression or unusually broad technical ownership
• Early-stage or high-growth startup experience
• Terraform
• Distributed systems
• Data ingestion, ETL, or real-time processing infrastructure
• AI/ML infrastructure, including LLM inference or training infrastructure
• Security, compliance, data governance, or regulated-industry environments
• Datadog, Prometheus, Grafana, or similar observability platforms
• AWS SageMaker, Bedrock, or related AI infrastructure
• Experience working across multiple cloud environments