AI Engineer Sr.

Job Description

Skill Set

• Python,LLM,Langchain,LlamaIndex,AI driven SDLC tooling,(LangChain,or similar)

• Total Experience :

• 5.00 to 10.00 Years

• No of Openings :

• 1

• Job Post Date :

• 08/06/2026

• Job Expiry Date :

• 31/08/2026

• Domain :

• IT

• Location :

• MEXICO CITY [Mexico]

• Job Reference No :

• 4082810

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• Job Summary

• AI Engineer Mid/ Senior

Build the GenAI powered produc t 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 frork and tool use, evals and guardrails, and LLM application development for internal business functions such as marketing automation and BI agents.

What you will do:

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.

Track specific required skills:

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.

Track specific Nice to have skills:

Experience with e commerce platforms, product catalogs, or high traffic consumer applications.

Exposure to MLOps tooling or model deployment pipelines.

Experience working in distributed teams across the US, China, and Latin America.

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