Software Engineer: Cloud Infrastructure

Big Wombat LLC; United States; Remote; USD 215,000 - 325,000; Full time

Benefits offered by this job

Meaningful equity

Job summary

Yaklabs is building a desktop AI application that turns knowledge workers into AI power users, with one surface for agentic AI work. The team collaborates in New York City for product and design, while several engineering roles are remote. This is an early-team opportunity with founder-level impact and meaningful equity.

We’re hiring for cloud infrastructure, telemetry, billing, and deployment ops to support durable, secure, multi-tenant agent platforms across local and cloud environments.

Qualifications

• You’ve built and operated production cloud infrastructure, and you’ve been on call for systems real users depend on.

Responsibilities

• Build and operate cloud-deployed agent infrastructure: running agents server-side, isolating their execution, and scaling that fleet up and down.
• Build and operate the model gateway: routing, rate limiting, fallback, cost controls. The single entry point between local clients and every inference provider.
• Design and build telemetry ingestion: structured events from thousands of local clients, queryable, exportable, and auditable.
• Build usage metering and billing: per-tenant tracking, cost attribution, metering that’s accurate enough to bill on.
• Own deployment infrastructure: CI/CD, release pipelines, rollback, environment management.
• Design the multi-tenancy model: data isolation, tenant boundaries, access controls.
• Build the data governance layer: retention policies, deletion, compliance hooks.

Job description

Engineering, Remote (US or EU timezones), Full-time

You build and operate the cloud side of Bonsai: the part that keeps working when the laptop is closed, and the part a company’s security team reads before it signs.

Problems you’ll work on

These are examples, not lanes. You will move between them, while taking real ownership of the ones that match your interests.

• Agents that move between local and cloud: An agent starts on a user’s laptop, inside an extensible runtime with plugins, private context, and work already in flight. How do we run it in the cloud so that work can continue when the laptop is gone, then let other people reach it as a shared agent, without leaking one person’s data, credentials, or authority to another?
• Durable agent execution: Agent runs may last for hours and move between a laptop and the cloud; how do we make their state, messages, and tool side effects survive sleep, network partitions, crashes, deploys, and retries without losing or duplicating work?
• Safe extensibility in the cloud: How do we run third-party plugins and agent-authored code with useful tools while isolating tenants, secrets, data, and failures?
• Reliable event delivery: How do webhooks and events from GitHub, Slack, and other services reach the right agent when its client may be asleep, offline, behind NAT, or continuing in the cloud?

What you’ll do

• Build and operate cloud-deployed agent infrastructure: running agents server-side, isolating their execution, and scaling that fleet up and down.
• Build and operate the model gateway: routing, rate limiting, fallback, cost controls. The single entry point between local clients and every inference provider.
• Design and build telemetry ingestion: structured events from thousands of local clients, queryable, exportable, and auditable.
• Build usage metering and billing: per-tenant tracking, cost attribution, metering that’s accurate enough to bill on.
• Own deployment infrastructure: CI/CD, release pipelines, rollback, environment management.
• Design the multi-tenancy model: data isolation, tenant boundaries, access controls.
• Build the data governance layer: retention policies, deletion, compliance hooks.

Who you are

• You’ve built and operated production cloud infrastructure, and you’ve been on call for systems real users depend on. You have opinions about what breaks and why.
• You treat tenant isolation as a design constraint that runs through every layer.
• You care about cost. You’ve built metering or cost attribution systems, and you keep spend visible and under control.
• Strong networking fundamentals. You understand the path between a local client and a cloud service, and you know where it can fail.
• You build for operability. You’ve owned systems where observability, deployment, and rollback were afterthoughts, and you’ve fixed them.

Bonus

• You’ve built a model gateway or LLM proxy in production.
• You’ve dealt with enterprise compliance requirements (SOC 2, ISO 27001, or similar).
• You’ve managed large compute fleets and VM infrastructure.

About Yaklabs

Yaklabs is building a desktop AI application that turns knowledge workers into AI power users, without docs, API keys, or knowing what to ask for. One surface for agentic AI work: proactive, personalized, progressively powerful. The gap between AI power users and everyone else isn’t talent, it’s setup. We close it.

The team: Alex Goddijn spent four years at Palantir, then founded an agent harness company that was acquired by Poolside AI. Seb Goddijn led internal AI at Ramp. We’re building Bonsai so that kind of leverage isn’t limited to companies with their own internal AI team.

We have funding. Product and design work in person in New York City, and some engineering roles are remote. Small team, high intensity, no passengers.

The deal

• Early team. $215k to $325k base salary for US-based hires, plus meaningful equity.
• In person in New York City for product and design roles. Some engineering roles are remote, and each posting lists its location.
• You’ll shape the product, the culture, and the company. This is a founding-team role.