Infrastructure Engineer - AI Systems & Platform Reliability
At Doe, we’re deploying autonomous AI agents that operate mission-critical workflows across private equity-backed rollups - starting with DSOs, then expanding into veterinary, ophthalmology, and med spas. These agents need to be fast, resilient, auditable, and secure.
We're looking for an in-person infrastructure engineer to own the reliability, scalability, and performance of our platform as we scale. You’ll work at the intersection of LLM infrastructure, real-time agent orchestration, and enterprise-grade systems.
What you’ll do:
Design, build, and maintain our cloud infrastructure (preferably GCP or AWS)
Build a robust observability stack: logs, traces, metrics, and alerts
Improve infra to support LLM latency, multi-agent concurrency, and uptime guarantees
Harden our security, auth, and data access posture across customer deployments
Enable internal tooling for agent testing, rollout, and auditability
You might be a fit if you:
Have 4+ years of experience in infra, DevOps, or platform roles
Have worked with Kubernetes, Terraform, Postgres, VPCs, and serverless stacks
Understand LLM system demands—e.g., context caching, vector stores, tool routing
Care about system health, observability, and clean abstractions
Want to work in person with a tight-knit team at the frontier of AI + enterprise
Why Doe?
We're an in-person team building ambitious AI systems for $1T+ verticals
You’ll shape the foundation of a platform that powers real autonomy
Competitive salary, meaningful equity, and $25K+ in elite benefits (food, travel, wellness)
Strong culture of execution, engineering rigor, and curiosity
Average salary estimate
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