Backend Engineeer (Infra)

Our client is an AI talent matchmaking company based in NYC. The big idea is building an agent ecosystem for talent, where every person has an agent representing them, and every company has an agent that actually knows what it needs, so the two can talk directly instead of relying on resumes and job descriptions that lose most of the real signal along the way.

We are looking for a Backend Infrastructure Engineer with 3–6+ years of experience to own and scale the core infrastructure powering our client's enterprise product. You'll be one of the first engineering hires at a freshly funded ($4M seed) AI-native startup building the context layer for human work — managing multi-tenant deployments, handling 800M+ rows of data, and making architectural decisions that define the platform.

What will you be doing?

• Optimizing and hardening the existing AWS-based product infrastructure to support rapid scaling of customer deployments
• Building and maintaining multi-tenant deployment architecture — managing permissioning, data isolation, and redeployability across enterprise customers
• Owning the infrastructure-as-code layer (Terraform, Kubernetes, Docker) and making decisions on what services and patterns enable easier scaling
• Building new features and capabilities as signal comes in from design partners
• Encoding learnings from bespoke customer deployments back into the core product

Experience

• 3 - 6 years of experience in backend/infra engineering
• Built and maintained production infrastructure at scale with high ownership
• Managed multi-tenant deployments and large-scale data in a production environment
• End-to-end ownership of backend systems — not just contributed to a larger team's infrastructure

Must have:

• AWS or GCP production experience with containerized deployments (Docker, Kubernetes, or Fargate)
• Infrastructure-as-code experience (Terraform or similar)
• Uses AI coding tools (Cursor, Copilot, etc.) in daily workflow

Nice to have:

Founding engineer or early engineer at a startup (Series A/B or earlier)

Education

Bachelors of Computer Science (or Masters) , Bachelors of Computer Engineering (or Masters), or equivalent technical degree