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Senior AI Engineer
Patsnap · Singapore · Not Specified
Quick Summary
- Design and build company-wide AI knowledge infrastructure and context management system.
- Develop scalable LLM application architecture including RAG pipelines and vector database integration.
- Own end-to-end technical delivery of internal AI tools from backend to deployment and monitoring.
Full Description
Role Overview
This role will be the technical foundation builder for the company’s AI transformation. You will design and build the company-wide knowledge infrastructure and context layer that powers future AI applications. This is a highly hands-on role requiring strong backend engineering capability, LLM application experience, product sense, and the ability to operate independently in a fast-moving, ambiguous environment.
- Design and build the company-wide AI knowledge infrastructure, including company wiki, internal knowledge base, retrieval layer, and context management system.
- Develop scalable LLM application architecture, including RAG pipelines, vector database integration, prompt workflows, API services, monitoring, and deployment.
- Own the end-to-end technical delivery of internal AI tools, from backend architecture and basic frontend integration to deployment, testing, and monitoring.
- Work closely with business, brand, PR, IR, and leadership stakeholders to translate ambiguous business needs into practical AI systems and technical roadmaps.
- Optimize system performance, including token efficiency, latency, caching strategy, retrieval quality, data architecture, and model inference flow.
- Evaluate and integrate AI coding tools, LLM frameworks, vector databases, and third-party APIs to improve development efficiency and product quality.
- Mentor junior engineers or interns when needed, and help establish technical standards, documentation practices, and reusable engineering workflows.