Senior AI Product Operations Manager (LLM / AIOS)
remotepeople- Posted 17 hours ago
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Job Description
About the Role
Our client is seeking an experienced AI Product Operations Manager to lead end-to-end product operations for our global AI-driven smart home system. In this role, you will focus on LLM algorithm capability iteration, C-end user experience, and ambient intelligence across key international markets (Europe, Americas, Southeast Asia, and India). You will turn user insights into actionable strategies that evolve our smart ecosystem from passive Q&A into an active, context-aware home experience.
Key Responsibilities
- Global AI User Insight & Strategy: Research AI interaction habits, home device usage behaviors, and regional preferences across global markets. Benchmark against industry leaders to identify opportunities in wake-free dialogue, multi-turn conversations, on-device AI, and proactive smart scenarios.
- Core C-End Experience Operations: Own user experience operations for the AI Homepage, personalized recommendations, ambient intelligence, and scenario-based proactive services. Define trigger rules, delivery strategies, and service scheduling tailored to daily household routines.
- LLM Algorithm Quality & Governance: Oversee corpus production, annotation standards, model evaluation, hallucination mitigation, and quality assurance for cloud-edge integrated models.
- Data-Driven Iteration: Identify product bottlenecks using user behavior, conversation data, and negative feedback. Run A/B tests to boost AI feature adoption, user retention, and overall satisfaction.
Qualifications
- Experience: Bachelor's degree with 3+ years in AI product operations, LLM experience operations, or global C-end intelligent product operations.
- Technical & Product Acumen: Solid understanding of LLMs, intelligent interaction, personalized recommendation systems, and scenario-based intelligence. Ability to diagnose model issues and break down UX bottlenecks.
- Data Competency: Strong analytical skills in root-cause analysis, data decomposition, and experiment iteration.
- Communication: Fluency in English (reading and writing) for independent market research, user studies, and cross-border collaboration.
Preferred Qualifications
- Experience with large-screen/smart home hardware, Ambient AI, or cloud-edge collaborative AI systems.
- Hands-on experience with LLM evaluation, prompt engineering, corpus operations, or AI Agent scenario implementations.
- Familiarity with global smart device AI product portfolios (e.g., Google TV, Roku, Amazon, Samsung).
More Info
Key Skills
personalized recommendation systems
LLM algorithm capability iteration
data decomposition
scenario-based intelligence
prompt engineering
on-device AI
AI Agent scenario implementations
model evaluation
corpus operations
hallucination mitigation
cloud-edge integrated models
LLM evaluation
root-cause analysis
