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
