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# Gen-AI Senior Software Engineer, Full Stack

- **Company:** iHerb
- **Location:** Shanghai, WV, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), Artificial Intelligence, Automation of Tests, Code Generation, Software Quality, Code Review, Encodings, Continuous Integration, Cursor, Python (Programming Language), Machine Learning, Node.Js, Systems Development Life Cycle, Search Technologies, Software Engineering, Data Logging, GitHub Copilot, LangChain, ReactJS, Large Language Models, Claude Code, Prompt Engineering, Generative AI, Backend, Langfuse — LLM Observability and Analytics Platform, Solid Principles, Production Code, Machine Learning Operations, Front End Software Development, Restful APIs, Golang, Microservices
- **Published:** October 20, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/psz9r0oyzf

## About the Role

* 8+ years of software engineering experience. Fully autonomous; drives technical decisions within the team; mentors junior engineers.
 * Full stack experience. Backend development proficiency in one or more of: Python, nodejs, Go, Java. Python is the primary stack today. React or equivalent modern frontend framework.
 * Practical experience with LLM/ML orchestration framework such as LangGraph, LangChain, Langfuse or MLFlow.
 * Deep understanding of LLMs, including prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques.
 * Proficiency in vector databases and embedding-based search technologies.
 * REST API design and microservice patterns.
 * AI-driven SDLC : hands-on experience shipping production code with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor. The bar is not awareness; it is daily use in delivering real software.
 * Production ownership: experience owning features end-to-end from spec through deployment, observability, and on-call. Engineers here own what they ship; there is no separate ops handoff.
 * Code quality fundamentals: strong grasp of software design principles, automated testing, code review, and CI/CD.

NICE TO HAVE

 * Contributions to internal developer tooling, golden path standards, or SDLC process improvements.
 * Experience with e-commerce platforms, product catalogs, or high-traffic consumer applications.
 * Experience working in distributed teams across different time zones / geographies.
 * Track record of documenting architectural decisions, writing RFCs, or contributing to engineering wikis.

## Description

We are seeking seasoned full stack engineers with a passion for building AI-driven solutions to join our Shanghai team. These are full-ownership IC roles: you write production code, own features end-to-end from spec through deployment, operations, and observability, and you participate in on-call rotation for what your team ships. There is no handoff to a separate ops or reliability function; engineers own the full lifecycle. Test automation is built into how we ship using AI-driven tooling and the golden path., * Prototype, design, and develop innovative AI/ML solutions end to end, ranging from bots,agents to tools with a focus on generative models, large language models (LLMs), scalability, cost-efficiency, and compliance with industry standards .

 * Use AI-driven SDLC tooling such as Claude Code as a core part of your daily workflow, including code generation, spec-to-code translation, and automated test creation.
 * Write and maintain automated tests; quality is built in, not handed off.
 * Review pull requests, maintain code standards, and contribute improvements to the shared golden path.
 * Collaborate with product and design to refine specs before and during implementation.
 * Instrument services with logging, metrics, and alerts; participate in on-call rotation and own incident response for catalog services.
 * Build and maintain AI pipelines, including data digestion, preprocessing,, and monitoring.
 * Ensure AI systems comply with data privacy and security regulations.
 * Explore and implement prompt engineering, fine-tuning, and evaluation strategies.
 * Continuously monitor AI workflow performance metrics and implement improvements.