Storage Platform R&D Engineer（Database Intelligence）- rednote

About Rednote

rednote is one of the world's most trusted platforms, where over 350 million people share how they actually live, travel, create, and discover. In a world of infinite content, what sets rednote apart is its source: real human experience, honestly lived and generously shared — one note at a time. We are now writing our global chapter, and this team is at the forefront.

What You'll Do

• Lead Storage Cloud Platform Architecture & Core Development — Drive the architectural evolution and core module development of Rednote's storage platform. Explore AI-Native architectures for intelligent storage solutions and transform the platform from a tooling-focused system into an intelligent platform.
• Build Intelligent Operations System — Own the technical planning and execution of a self-service storage and database management platform. Leverage large language model capabilities to build an intelligent operations agent that supports natural language interaction, lowering the barrier to database operations.
• Drive Intelligent Operations Transformation — Re-architect the automated operations platform based on LLM Agent technologies to build a self-diagnosing, self-healing, and self-optimizing intelligent operations system — enabling a shift from manual operations to fully automated, zero-touch operations.
• Deepen AI + Database Innovation — Lead practical LLM adoption in database domains, including: intelligent SQL optimization, anomaly detection and root cause analysis, capacity prediction and auto-scaling, and intelligent alerting noise reduction.
• Elevate Product Experience — Continuously track leading AI Agent products (such as Cursor, Claude Code, Devin, etc.) and integrate advanced AI interaction paradigms into the database storage platform to deliver industry-leading intelligent operations experience.

Qualifications

• Strong Engineering Foundation — Proficient in at least one backend programming language (Go / Java / Python); familiar with frontend frameworks (Vue / React); hands-on experience building Agent applications using large model APIs (OpenAI, Claude, Qwen, etc.).
• Deep Storage Domain Experience — Hands-on experience with distributed storage; familiar with the principles and operational practices of at least two of: distributed KV/cache, MySQL, distributed databases, graph databases, table storage, or object storage.
• AI Application Development — Proficient in the LLM application development stack: RAG, Prompt Engineering, Function Calling, and multi-agent frameworks (LangChain, LlamaIndex, AutoGen, etc.); experience shipping complete projects.
• Product Thinking & AI Fluency — Deep practical experience with AI tools such as Cursor, Claude Code, GitHub Copilot, etc.; ability to translate AI capabilities into product features and engineering delivery.
• Strong Soft Skills — Excellent at breaking down requirements and driving technical execution; strong cross-team communicator; customer-oriented mindset and strong sense of ownership; forward-looking judgment on AI in infrastructure; fluent in both English and Chinese (spoken and written).
• Bonus — A technical blog, open-source contributions, or AI competition awards are a plus; hands-on experience in AIOps, intelligent operations, or LLM Agent development is highly preferred.

The Pay Range For This Role Is

200,000 - 400,000 USD per year(Palo Alto, CA)