About the RoleThis is a high-ownership engineering role on a small, fast-moving product team building real-world AI and automation products. You'll own customer-facing features end-to-end - from design through shipping and iteration - making both product and engineering decisions with speed and strong judgment, with minimal PM overhead.
What You'll Do- Own features end-to-end across design, shipping, and iteration.
- Make independent product and engineering decisions without heavy process support.
- Build and maintain backend systems, APIs, data models, and automation pipelines.
- Integrate with external tools, legacy systems, and messy third-party services.
- Design workflows and orchestration for AI/automation-driven products.
- Debug production issues and apply strong engineering judgment under pressure.
- Collaborate closely with founders, customers, and cross-functional stakeholders in a hybrid SF setting.
- Contribute across the full stack when needed, with a clear emphasis on backend ownership.
What We're Looking For- Background as an early or founding engineer, startup generalist, or strong product/backend engineer at a scaling startup.
- Demonstrated track record of shipping real products, ideally in 0-to-1 or ambiguous, messy environments.
- Solid experience with backend systems, APIs, data modeling, automation, and third-party integrations.
- Experience designing, implementing, and maintaining data models and automation pipelines.
- Strong debugging instincts and production troubleshooting skills.
- Applied AI or workflow/orchestration experience (e.g. agentic workflows, RAG, LLM-enabled features) is a plus.
- Python experience is a plus; modern web/backend stacks are acceptable - engineering quality matters more than specific stack.
- Genuine motivation for early-stage startup work and comfort with ambiguity and pace.
- Based in San Francisco or willing to relocate; on-site presence in SF required.
Compensation & BenefitsBase salary up to
$275,000 USD annually, plus meaningful equity. Visa sponsorship is not available.
LocationOn-site in
San Francisco, CA. Candidates must be based locally or willing to relocate.
