Senior Software Engineer II – AI

🕒 July 10

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Logo of iHerb

iHerb

1001 - 5000 employees

🛍️ eCommerce

🛒 Retail

🧘 Wellness

eCommerce • Retail • Wellness

iHerb is an online retailer founded in 1996 that provides a curated selection of health and wellness products to consumers worldwide. The company focuses on vitamins, natural supplements and remedies, sports nutrition, natural and dry foods, and environmentally friendly goods, with a mission to make health and wellness accessible, affordable, and convenient. iHerb operates as an e-commerce business with a retail focus and emphasizes customer experience and a values-driven company culture.

📋 Description

• The Sr. Software Engineer II - AI will lead the build of GenAI-powered product experiences and the shared AI platform infrastructure that powers them. • This includes RAG pipelines over the iHerb catalog and customer reviews, LLM-driven personalization, a conversational Wellness Agent, agentic workflow systems, and the evals and MLOps layer that makes AI features production-grade and repeatable. • Design, build, and operate production AI features: RAG pipelines, LLM-driven recommendations, conversational agents, or agentic workflow automation. • Build the shared AI platform layer: retrieval infrastructure, eval frameworks, model monitoring, guardrails, and observability. • Write LLM applications and integrations with marketing platforms, BI tools, or customer-facing product surfaces.

🎯 Requirements

• Generally requires a minimum of 10+ years of software engineering experience. • AI-driven SDLC : hands-on experience shipping production code with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor. • Full-stack awareness: comfortable contributing across layers of the stack when needed. • Production ownership: experience owning features end-to-end from spec through deployment, observability, and on-call. • Code quality fundamentals: strong grasp of software design principles, automated testing, code review, and CI/CD. • Fully autonomous; drives technical decisions within the team; mentors junior engineers. • Python proficiency; comfortable building and operating production LLM applications. • Hands-on experience with at least one specialization: RAG and retrieval systems, LLM evaluation, agentic frameworks (LangChain, LlamaIndex, or similar), or LLM-based workflow automation. • Understanding of prompt engineering, context window management, and LLM output quality tradeoffs. • Familiarity with vector databases, embedding models, or semantic search.

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