# AI Agent Infrastructure Lead

**Company**: Sphere
**Location**: San Francisco HQ
**Work arrangement**: onsite
**Experience**: senior
**Job type**: Full time
**Salary**: $230K – $260K
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q11312826

**Apply**: https://jobs.ashbyhq.com/sphere/9e1defbe-b135-4117-90b0-06548fa75fa7?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_60d9a00e-729

## Description

We're looking for an engineer to lead our internal AI agent enablement efforts. You'll build the systems that let AI agents safely and effectively increase velocity across Sphere, starting with engineering and expanding into ops, customer success, tax research, and implementation workflows.

Within days: Ship AI agent features that help Sphere's engineering team use agents more effectively and responsibly. Iterate on versions of Sphere's agent sandbox environments. Create workflows where agents can inspect the codebase, run local infrastructure, make changes, run tests, and prepare work for human review. Work directly with engineers to identify high-leverage internal workflows where agents can create immediate velocity.

Within months: Lead Sphere's internal efforts to enable AI agents to act more autonomously across engineering, ops, customer success, tax research, and implementation. Build 'Goose' for Sphere: the internal AI agent layer that helps agents understand and operate across Sphere's systems. Own the infrastructure, tooling, and workflows that let agents safely take on more complex internal work over time. Establish the patterns for how Sphere uses agents internally, including context, permissions, review, observability, and escalation.

## Skills

### Required
- Experience building production-quality software
- Experience in AI agents, coding agents, internal developer tooling, or AI agent enablement
- Comfort working across backend systems, infrastructure, local development environments, CI, and internal tools
- Strong judgment around autonomy, safety, permissions, and human review
- High agency. You can take a vague internal problem and turn it into a working system people actually use

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Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/sphere/9e1defbe-b135-4117-90b0-06548fa75fa7?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)