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Prepare system design for high-traffic retail, coding depth, and how you’d apply AI safely to catalog, search, or recommendations. Be ready to discuss production ML tradeoffs and remote collaboration.
Strong fit if you want senior AI engineering at a large wellness e-commerce platform with global scale and public growth/IPO narrative—less so if you need dense on-site culture signals or published pay bands (not in this data).
As a Sr. Software Engineer II focused on AI at iHerb, expect to design and ship ML-backed features for a large e-commerce catalog—data pipelines, model integration, and production services that support search, personalization, or content quality—while collaborating with product and platform teams on reliability and scale.
Strengthen software fundamentals and practical ML/product engineering.
Yes—the listing is remote in the USA.
It sells vitamins, supplements, and wellness goods online (iherb.com), founded 1996, ~3,000 employees.
Reports cite ~$2.9B fiscal 2025 net sales and work toward a possible IPO.
Website: iherb.com
Public cache only — not an employee review.
iHerb is hiring a remote Sr. Software Engineer II – AI to spearhead the development of generative-AI product experiences and the platform that powers them. This full-time role, open to candidates across the USA, puts you at the center of how millions of shoppers discover wellness products through intelligent, AI-driven features. About the Role As a Sr. Software Engineer II – AI at iHerb, you will own the design and operation of production GenAI capabilities — from retrieval-augmented generation (RAG) over our product catalog and customer reviews to LLM-powered personalization, a conversational Wellness Agent, and agentic workflow automation. You will also help build the shared AI platform: retrieval infrastructure, evaluation frameworks, monitoring, guardrails, and the MLOps layer that keeps these features reliable and repeatable. Specialization tracks span RAG and personalization, agent frameworks and tool use, evals and guardrails, and LLM applications for internal functions like marketing automation and BI agents. Key Responsibilities Build and operate production AI features such as RAG pipelines, LLM-driven recommendations, conversational agents, and agentic automation. Develop the shared AI platform layer: retrieval systems, eval frameworks, model monitoring, guardrails, and observability. Create LLM applications and integrations across marketing platforms, BI tools, and customer-facing surfaces. Measure model and feature quality with structured evals, iterating on prompts, retrieval strategies, and model selection using data. Apply AI-assisted SDLC tooling like Claude Code as a daily practice for both AI and non-AI work. Partner with the Personalization team to align GenAI features with existing ML signals, and document design decisions and lessons learned. Own end-to-end observability — latency, cost, quality drift, and error rates — and participate in on-call rotation and incident response. Qualifications 10+ years of software engineering experience; Bachelor's in Computer Science or equivalent experience preferred. Hands-on, daily use of AI-assisted development tools (Claude Code, GitHub Copilot, or Cursor) to ship real production code. Python proficiency and experience building and operating production LLM applications. Depth in at least one area: RAG and retrieval, LLM evaluation, agentic frameworks (LangChain, LlamaIndex, or similar), or LLM workflow automation. Solid grasp of prompt engineering, context-window management, vector databases, embeddings, and semantic search. Full-stack…
Generated for personal interview prep · 2026-07-16 UTC · getajob.ai