Sr. LLM Application Engineer (AI Agents)

Tencent•Palo Alto, CA

1d•Onsite

About The Position

This role involves leading the design and development of Agent-native platforms tailored for R&D availability, environment governance, and AIOps, driving the implementation of generative AI technologies to solve complex engineering challenges. It also includes building and maintaining enterprise-grade vertical domain knowledge bases, implementing advanced retrieval and integration strategies to empower intelligent agents with specialized domain expertise. Furthermore, the position focuses on integrating Large Language Model (LLM) capabilities with internal toolchains and standardized APIs, encapsulating these into reusable intelligent components to establish a centralized AI capability hub, boosting overall R&D and operational efficiency.

Requirements

Education: Bachelor’s degree or higher in Computer Science, AI, Software Engineering, or a related field.
Core Experience: Proven experience in LLM application development, with a strong track record in AI Agent architecture or RAG system optimization.
Technical Expertise: Deep understanding of AI Agent paradigms, RAG optimization, and standardized tool-use protocols; familiar with the entire pipeline from data processing and vectorization to intelligent generation.
Professionalism: Passionate about driving business efficiency through AI; excellent autonomous learning skills, logical thinking, and cross-functional collaboration capabilities.

Nice To Haves

Domain Knowledge: Background in Cloud Computing, IaaS/PaaS, DevOps automation, or AI-driven R&D efficiency.
Collaborative Design: Familiar with Multi-Agent System (MAS) design and standardized agent-to-agent communication protocols/orchestration frameworks.
Community Contribution: Active contributor to open-source AI projects or a track record of high-quality technical publications in AI engineering.
Production Experience: Proven experience in leading or playing a key role in deploying production-grade AI Agent systems.

Responsibilities

Platform Architecture Design: Lead the design and development of Agent-native platforms tailored for R&D availability, environment governance, and AIOps; drive the implementation of generative AI technologies to solve complex engineering challenges.
Knowledge Engineering: Build and maintain enterprise-grade vertical domain knowledge bases; implement advanced retrieval and integration strategies to empower intelligent agents with specialized domain expertise.
AI Capability Center: Integrate Large Language Model (LLM) capabilities with internal toolchains and standardized APIs; encapsulate these into reusable intelligent components to establish a centralized AI capability hub, boosting overall R&D and operational efficiency.