Senior AI Engineer - Lead Production LLM Agents (Singapore)

Patsnap; Singapore; On-site; SGD 150,000 - 230,000; Full time

Job summary

Patsnap's Materials team builds AI systems that help R&D scientists and engineers search, extract, and reason over materials science and patent data. You will own the agentic layer of our products end-to-end: LLM-powered agents, tools (MCPs), and the evaluation frameworks that prove they beat general-purpose AI for our customers.

You will be the AI engineer for this team — sole owner of the agentic stack, working directly with product managers, materials domain experts, and our platform team.

Qualifications

• Degree in engineering, computer science, or a quantitative/physical science — or equivalent practical experience.
• 5+ years of software/ML engineering, including 2+ years building LLM-based systems that run in production.
• Experience designing evaluations for LLM/agent systems with clear metrics and pipelines.
• Experience instrumenting, monitoring, and debugging live AI services with observability tools.
• Strong Python; able to independently build and deploy services.

Responsibilities

• Design, build, and productionize agentic systems (multi-step reasoning, tool orchestration, guardrails) for materials science search, Q&A and information extraction.
• Develop, integrate and maintain memory systems, MCP servers and agent skills in a multi-agent environment.
• Build evaluation frameworks with domain experts to measure answer quality, extraction accuracy, and retrieval performance.
• Own production reliability & observability of agents you develop.
• Advise adjacent teams on agentic and search system design; flag technical risk and feasibility during roadmap planning.

Skills

Python

LLM-based systems

Evaluations design

Production services

Education

Engineering/CS degree or equivalent

Tools

OpenTelemetry

Arize Phoenix

Langfuse

Datadog

Job description

Patsnap's Materials team builds AI systems that help R&D scientists and engineers search, extract, and reason over materials science and patent data. You will own the agentic layer of our products end-to-end: LLM-powered agents, tools (MCPs), and the evaluation frameworks that prove they beat general-purpose AI for our customers.

You will be the AI engineer for this team — sole owner of the agentic stack, working directly with product managers, materials domain experts, and our platform team.