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

re-zoo-me; Palo Alto, Northern (CA, KY); Hybrid; USD 200,000 - 400,000; Full time

Job summary

Rednote is seeking a senior backend engineer to lead the storage platform's architecture and core development, driving evolution toward an AI-native storage solution.

You will build an intelligent operations system, leveraging large language models to create a self-service storage and database management platform, and transform automated operations with LLM Agent technologies.

Qualifications

• Strong engineering foundation in at least one backend language (Go/Java/Python).
• Familiar with frontend frameworks (Vue/React) and building agent apps using large model APIs (OpenAI, Claude, Qwen).
• Experience with distributed storage and core storage primitives.
• Experience with AI toolchains, RAG, prompt engineering, function calling, and multi-agent frameworks.
• Ability to translate AI capabilities into product features and engineering delivery.
• Fluent in English and Chinese (spoken and written).

Responsibilities

• Lead Storage Cloud Platform Architecture & Core Development and drive architectural evolution.
• Build an intelligent operations system with self-service storage and database management; leverage LLM capabilities.
• Re-architect automated operations with LLM Agent technologies for self-diagnosing and self-healing systems.
• Deepen AI + Database innovation with intelligent SQL optimization, anomaly detection, and auto-scaling.
• Elevate product experience by integrating advanced AI interaction paradigms into the platform.

Skills

Go

Java

Python

Vue

React

Agent applications

Tools

LangChain

LlamaIndex

AutoGen

OpenAI API

Qwen

Job description

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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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

1. 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.).
2. 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.
3. 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.
4. 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.
5. 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).
6. 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)