Principal Engineer – AI Platform

🕒 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

• Define and own the AI platform architecture: retrieval infrastructure, model lifecycle, evals framework, guardrails, and GenAI product feature design. • Lead the build of the shared AI platform layer consumed by all AI product features and reusable by internal business teams. • Hands-on contributor: build production AI systems, write proofs of concept, and validate architecture through working software. • Set and enforce technical standards for the AI Platform team; drive architecture reviews and model quality reviews. • Coordinate with the Personalization team to define clear boundaries between the GenAI product layer and existing ML personalization infrastructure. • Contribute AI platform-specific patterns and lessons into iHerb's shared AI-driven SDLC golden path. • Drive the hardest cross-cutting technical decisions across multiple teams and shared platform services. • Establish and evolve iHerb's AI-driven SDLC golden path: shared standards, Claude Code skills, guardrails, and automation patterns. • Lead complex multi-team technical efforts by coordinating architecture reviews, aligning peer Principals and EMs, and resolving competing approaches. • Mentor and raise the technical bar across the engineering organization through code review, architecture review, and direct coaching of senior engineers. • Represent engineering in cross-functional conversations with product, data science, security, and infrastructure. • Feed architectural decisions into the shared knowledge base so institutional knowledge compounds across the organization.

🎯 Requirements

• 10+ years of software engineering experience. • AI-driven SDLC: demonstrated use of AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor to ship production systems. • Experience designing and evolving large-scale distributed systems: APIs, data pipelines, event-driven architectures, or high-traffic platforms. • Track record of driving architectural standards, technical roadmaps, or platform initiatives that span multiple teams or organizations. • Deeply held opinions on code quality, observability, CI/CD, test automation, and maintaining velocity without accumulating hidden debt. • Able to write clear architecture documents, present to technical and non-technical audiences, and build consensus without formal authority. • Experience working in distributed teams across the US, China, and Latin America. • Production experience designing and operating AI platform systems: RAG pipelines, vector search, embedding infrastructure, or retrieval-augmented applications at scale. • Hands-on experience with LLM evaluation: building eval frameworks, defining quality metrics, and iterating on model and prompt quality using data. • MLOps experience: model deployment, monitoring, lifecycle management, and cost governance in a production environment. • Experience building and operating agentic systems using frameworks such as LangChain, LlamaIndex, or equivalent. • GenAI in production is required; prototype or research-only experience is not sufficient at this level. • High degree of accuracy and attention to detail. • Excellent organization skills and ability to multi-task.

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