Senior/AI Engineer

PATSNAP PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Patsnap PTE. LTD. is seeking an experienced software/ML engineer to own the end-to-end development of agentic systems. You will build scalable systems, define MCP server designs, and lead observability efforts in production.

Ideal candidates have strong software engineering fundamentals, 5+ years in ML/AI engineering, and experience deploying production-grade LLM-based services with robust telemetry and evaluation pipelines.

Qualifications

• Bachelor's degree in engineering, CS or related analytical field.
• 5+ years of software or ML engineering, incl. 1+ years building production LLM systems.
• Designed evaluations for LLM/agent systems with eval sets, metrics and human/LLM judgment pipelines.
• Instrumented, monitored, and debugged live AI services using observability tools.

Responsibilities

• Design, build, and productionize agentic systems for domain-specific tasks.
• Develop MCP servers (tool design, description and schema) to boost agent performance.
• Create evaluation frameworks with domain experts to measure answer quality and retrieval accuracy.
• Own production reliability and observability from instrumentation to model/provider evaluations.

Skills

Software engineering

System design

ML engineering

Observability

Education

Bachelor's degree in engineering or CS

Tools

OpenTelemetry

Arize Phoenix

Langfuse

Datadog

Job description

About the role

Patsnap's Materials team builds intelligent systems that help materials 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 from product development to implementing the observability tooling and feedback loops to improve them continuously in production.

What you'll be doing

• Design, build, and productionize agentic systems that beat general-purpose AI agents in our domain.
• Develop MCP servers (tool design, description and schema) that improve the performance of other agents on tasks in our domain.
• Build evaluation frameworks with domain experts to measure answer quality, retrieval performance and scientific accuracy.
• Own production reliability & observability of agents you develop from instrumentation to model/provider evals.

Requirements

• Bachelor's degree in engineering, computer science or any field where analytical and critical thinking was demonstrated.
• 5+ years of software or ML engineering, including 1+ years building and maintaining production LLM-based systems.
• Designed evaluations for LLM or agent systems - eval sets, quality metrics, human-expert and/or LLM-judge pipelines.
• You have instrumented, monitored, and debugged live AI services (e.g., OpenTelemetry, Arize Phoenix, Langfuse, Datadog, or similar).
• Strong software engineering and system design fundamentals.

Nice to have

• API/SDK product or MCP (Model Context Protocol) server design experience.
• Materials science, chemistry, or patent/IP domain exposure.