Sr. LLM Application Engineer (AI Agents)
Description
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. Build and maintain enterprise-grade vertical domain knowledge bases; implement advanced retrieval and integration strategies to empower intelligent agents with specialized domain expertise. 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.
Responsibilities
- 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
- Build and maintain enterprise-grade vertical domain knowledge bases
- Implement advanced retrieval and integration strategies to empower intelligent agents with specialized domain expertise
- 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
Requirements
- Bachelor’s degree or higher in Computer Science, AI, Software Engineering, or a related field.
- Proven experience in LLM application development, with a strong track record in AI Agent architecture or RAG system optimization.
- 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.
- Passionate about driving business efficiency through AI; excellent autonomous learning skills, logical thinking, and cross-functional collaboration capabilities.
- Background in Cloud Computing, IaaS/PaaS, DevOps automation, or AI-driven R&D efficiency (Preferred).
- Familiar with Multi-Agent System (MAS) design and standardized agent-to-agent communication protocols/orchestration frameworks (Preferred).
- Active contributor to open-source AI projects or a track record of high-quality technical publications in AI engineering (Preferred).
- Proven experience in leading or playing a key role in deploying production-grade AI Agent systems (Preferred).
Benefits
- Sign on payment (case-by-case basis)
- Relocation package (case-by-case basis)
- Restricted stock units (case-by-case basis)
- Medical, dental, vision, life and disability benefits
- Participation in the Company’s 401(k) plan
- 15 to 25 days of vacation per year (depending on tenure)
- Up to 13 days of holidays throughout the calendar year
- Up to 10 days of paid sick leave per year
