Staff Product Engineer - AI

Job Description Job Description Career Renew is recruiting for one of its clients a Staff Product Engineer - AI - this is a hybrid role in Sunnyvale, CA. Salary range: 200-250K USD yearly plus benefits and equity. Join a fast-growing AI company backed by prominent investors with thousands of users worldwide. Work directly with experienced Silicon Valley veterans who've built category-defining products and taken companies from startup to IPO. We're hiring a Staff Product Engineer - someone who takes a feature from idea to production with full ownership. A builder, not a reviewer. This role sits at the intersection of backend systems, product experience, and AI. You'll own complete product surfaces - APIs, data pipelines, and the LLM orchestration layer that ties it all together - and work directly with the founders to shape what gets built. If you close the gap between what's built and what customers actually need, this is for you.

What you'll do Own features end-to-end: scoping, architecture, implementation, and iteration based on user feedback Build backend systems powering AI-driven workflows — Python, FastAPI, PostgreSQL, Redis Ship LLM-native features: RAG pipelines, agentic workflows, prompt systems that operate on real data infrastructure Work on developer-facing surfaces: VS Code extensions, CLI tooling, dbt integrations, SQL intelligence Improve reliability and performance of production AI systems at scale Partner directly with founders and early customers to decide what to build next Requirements : 8+ years of experience as a product engineer or backend-leaning full-stack engineer. (Mandatory) Shipped features from idea to production, with impact to real users (bonus if data engineers are the end-users). (Mandatory) Worked at a startup or on a fast-paced small team within a larger org. (Mandatory) Experience interfacing directly with customers. (Nice-to-have) Previously a founding engineer or early engineering hire. (Nice-to-have) Strong Python backend fundamentals. (Mandatory) Built and shipped APIs as part of distributed systems.(Mandatory) Comfortable owning, maintaining, and optimizing production databases.(Mandatory) Familiar with LLM-native features (i.e., RAG pipelines, agentic workflows, prompt systems).(Nice-to-have)