Job description

ABOUT THE ROLE Join a small, high-ownership product team at an early-stage B2B SaaS startup as a backend-leaning product engineer. 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. This is a role for someone who thrives in ambiguity, moves fast, and cares deeply about shipping real products that customers use. WHAT YOU'LL DO - Own features end-to-end — from design through shipping and iteration — with minimal PM oversight. - Build and maintain backend systems, APIs, data models, and automation pipelines. - Integrate with external tools, legacy systems, and third-party services. - Design workflows and orchestration for AI/automation-driven product features. - Debug production issues and exercise strong engineering judgment under pressure. - Collaborate closely with founders, customers, and cross-functional stakeholders in a hybrid San Francisco setting. - Balance full-stack work when required, with a clear emphasis on backend ownership. WHAT WE'RE LOOKING FOR Required: - Backend-focused software engineering with hands-on experience designing, implementing, and shipping customer-facing features. - Demonstrated ownership of the full feature lifecycle — ideation, implementation, and iteration based on customer feedback. - Track record of shipping real products, ideally in 0-to-1 or ambiguous, fast-moving environments. - Strong cross-functional collaboration and communication skills. - Must be legally eligible to work in the US without employer sponsorship. - Based in San Francisco or willing to relocate; hybrid/in-office presence required. Nice to Have: - Experience with applied AI, agentic workflows, RAG pipelines, or LLM-enabled features. - Python proficiency (modern web/backend stacks considered — engineering quality matters more than specific stack). - Systems integration experience with external APIs and legacy platforms. - Early-stage startup experience or founding engineer background. Not a fit if you are: frontend-only, data/internal-tools-only, pure DevOps/SRE without product ownership, pure research ML without shipping experience, or primarily motivated by corporate titles. COMPENSATION & BENEFITS - Base salary: up to $275,000 depending on experience. - Equity: meaningful equity package. - No visa sponsorship available. LOCATION San Francisco, CA — hybrid/on-site. Candidates must be based in SF or willing to relocate.

Requirements

Must-haves

Own features end-to-end — from design through shipping and iteration — with minimal PM oversight.
Build and maintain backend systems, APIs, data models, and automation pipelines.
Integrate with external tools, legacy systems, and third-party services.
Design workflows and orchestration for AI/automation-driven product features.
Debug production issues and exercise strong engineering judgment under pressure.
Collaborate closely with founders, customers, and cross-functional stakeholders in a hybrid San Francisco setting.
Balance full-stack work when required, with a clear emphasis on backend ownership.
Backend-focused software engineering with hands-on experience designing, implementing, and shipping customer-facing features.
Demonstrated ownership of the full feature lifecycle — ideation, implementation, and iteration based on customer feedback.
Track record of shipping real products, ideally in 0-to-1 or ambiguous, fast-moving environments.
Strong cross-functional collaboration and communication skills.
Must be legally eligible to work in the US without employer sponsorship.
Based in San Francisco or willing to relocate; hybrid/in-office presence required.
San Francisco, CA — hybrid/on-site. Candidates must be based in SF or willing to relocate.

Nice-to-haves

Experience with applied AI, agentic workflows, RAG pipelines, or LLM-enabled features.
Python proficiency (modern web/backend stacks considered — engineering quality matters more than specific stack).
Systems integration experience with external APIs and legacy platforms.
Early-stage startup experience or founding engineer background.
Not a fit if you are: frontend-only, data/internal-tools-only, pure DevOps/SRE without product ownership, pure research ML without shipping experience, or primarily motivated by corporate titles.

Application prep

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