Sr. Software Engineer II - AI

Job Summary

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. Specializations within this track include: RAG and personalization, agent framework and tool use, evals and guardrails, and LLM application development for internal business functions such as marketing automation and BI agents.

• 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.
• Evaluate model and feature quality using structured eval frameworks; iterate on prompts, retrieval strategies, and model selection using data.
• Use AI‑driven SDLC tooling such as Claude Code as a daily practice for both AI and non‑AI code.
• Coordinate with the Personalization team to align GenAI product features with existing ML personalization signals.
• Document AI system design decisions, evaluation results, and operational lessons in the shared knowledge base.
• Own the observability of AI systems you build: latency, cost, quality drift, and error rates; participate in on‑call rotation and respond to production incidents.

• Hands‑on experience shipping production code with AI‑assisted development tools such as Claude Code, Git Hub Copilot, or Cursor.
• Full‑stack awareness: comfortable contributing across layers of the stack when needed; purely single‑layer specialists are not the target profile.
• Experience owning features end‑to‑end from spec through deployment, observability, and on‑call.
• 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 (Lang Chain, Llama Index, 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.
• High degree of accuracy and attention to detail.
• Excellent organization skills and ability to multi‑task.

• Exposure to MLOps tooling or model deployment pipelines.
• 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 globally distributed teams.
• Track record of documenting architectural decisions, writing RFCs, or contributing to engineering wikis.

• Experience with Microsoft Office Suite (Word, Excel, PowerPoint).
• Experience with Google Business Suite (Gmail, Drive, Docs, Sheets, Forms) preferred.

Generally requires a minimum of 10+ years of software engineering experience.

Bachelor’s Degree in Computer Science or related field preferred, or a combination of education and equivalent work experience.

Able to identify, troubleshoot and resolve problems quickly using sound judgment, poise and diplomacy. Ability to use judgment and reasoning skills, and determine when to elevate issues, as required, in a timely manner.

The physical demands described here are representative of those that must be met by a Team Member to successfully perform the essential functions of this job. While performing the duties of this job, the Team Member is regularly required to talk and hear. The Team Member is frequently…