Senior​/AI Infrastructure Engineer

About Echelon

Echelon is building the AI platform for Business Operations. Our goal is to automate the knowledge work of Biz Ops so one exceptional operator can deliver the leverage of an entire team, as Ramp and Rippling have done for Finance and HR.
Our platform combines passive process mining with a living ontology that maps how work happens across people, systems, documents, decisions, and outcomes. It connects structured and unstructured data trapped in fragmented, duplicative, and legacy enterprise systems, then turns that context into automated workflows and AI agents.
We are an early-stage company tackling a difficult technical problem at high speed. Engineers work directly with founders and customers, make decisions with incomplete information, ship production systems, and own the results. The pace, rate of change, and standards are high.

The mandate
Build the secure execution substrate for Echelon's agents. You will scale ep * * ​
What you’ll own
Design and operate sandbox lifecycle systems for agent code execution, browser work, document processing, and tool use.
Improve sandbox startup time, density, scheduling, warm pools, caching, and resource utilization.
Build fast, reliable file system primitives for ephemerate and persistent agent state, large artifacts, and concurrent workloads.
Enforce tenant isolation, network policy, secrets boundaries, quotas, and least-privilege access.
Make long-running agent jobs durable through checkpointing, retries, idempotency, cancellation, and recovery.
Scale orchestration and control-plane services through rapid workload growth and unpredictable bursts.
Build observability for resource pressure, execution failures, queue health, noisy neighbors, cost, and end-to-end latency.
Run load tests, capacity plans, failure drills, and incident reviews; fix root causes rather than adding fragile workarounds.

What you bring
5+ years building production infrastructure, distributed systems, developer platforms, or execution runtimes.
Hands-on ownership of containerized or virtualized workloads in a multi-tenant production environment.
Strong Linux systems knowledge across processes, file systems, networking, resource isolation, and performance debugging.

Experience with Kubernetes or a comparable scheduler, infrastructure as code, and cloud primitives on AWS or Azure.
Strong programming ability in Go, Rust, Type Script, Python, or another systems-oriented language.
Experience designing for retries, idempotency, back pressure, load shedding, observability, and safe rollouts.
Security instincts appropriate for executing untrusted or model-generated work.

Useful experience
Firecracker, gVisor, Kata Containers, name spaces/cgroups, seccomp, or eBPF.
Sandbox products such as E2B, Modal, Fly Machines, or custom epigenetic compute platforms.
FUSE, overlay file systems, content-addressed storage, snapshotting, distributed caches, or object storage.
Agent runtimes, code interpreters, browser automation, remote development environments, or CI execution systems.
BYOC, private networking, customer-managed deployments, or enterprise security reviews.
Inngest, Temporal, Kafka, NATS, or other durable workflow and event systems.

• Fully covered health, dental, and vision insurance.
• 401(k) plan.
• Team lunches and dinners in the office.
• Unlimited PTO.