| Location | San Francisco, California |
| Website | https://www.getclera.com/ |
This 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.
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.
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.
Base salary up to $275,000 USD annually, plus meaningful equity. Visa sponsorship is not available.
On-site in San Francisco, CA. Candidates must be based locally or willing to relocate.