Join a small, high-ownership product team at Unknown as a backend-leaning product engineer focused on building real-world AI and automation products. This role matters because you’ll own customer-facing features end-to-end, navigate messy integrations and legacy systems, and make product and engineering trade-offs with speed and strong judgment.

What you'll do

• Own features end-to-end from design through shipping and iteration.
• Make product and engineering decisions independently without heavy PM support.
• Execute under pressure and deliver high-quality engineering results, not just plans.
• 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.
• Work comfortably in a very small, fast-moving startup team with little structure.
• Balance full-stack work when required, with a clear emphasis on backend ownership.
• Debug production issues and exercise strong engineering judgment.
• Collaborate closely with founders, customers, and cross-functional stakeholders in a hybrid SF setting.

What Unknown is looking for

• Early engineer, founding engineer, startup generalist, or strong product/backend engineer from a scaling startup.
• Track record of shipping real products, ideally 0-to-1 or in ambiguous/messy environments.
• Experience with backend systems, APIs, data modeling, automation, and integrations.
• Applied AI or workflow/orchestration experience (agentic workflows, RAG, LLM-enabled features) is a plus.
• Python experience is a plus; modern web/backend stacks are acceptable—stack fit matters less than raw engineering quality.
• Demonstrated ownership of customer-facing features and close work with founders or customers.
• Clear motivation for early-stage startup work and comfort with ambiguity and speed.
• San Francisco based or willing to relocate; hybrid / in-office in SF required.
• Compensation can go up to $275k base plus meaningful equity.
• Not a fit: frontend-only, data-only/internal-tools-only, pure DevOps/SRE without product ownership, pure research/ML without shipping experience, or candidates motivated primarily by corporate titles.