Teams at NUS Enterprise

Build and operate AI-assisted workflows and system integrations for research administration. Responsibilities include developing REST and GraphQL connectors, agent tooling with deterministic guardrails, LLM-based intake and classification, milestone monitoring, testing, documentation, user acceptance, and presenting shipped solutions to leadership.

Build and evaluate benchmark datasets for LLM systems processing patent documents and deal-sourcing data. Responsibilities include reviewing and refining annotations, running blind-test evaluations, measuring extraction reliability, identifying hallucinations and edge cases, cataloging schemas, and preparing quality-acceptance reports. The role offers direct engineering supervision, stakeholder-facing projects, and deployment experience.

Build and ship internal AI-enabled applications, including data-review, deal-signal, service-monitoring, and patent/IP-management tools. Develop agents and automations connecting internal systems, integrate LLM-based judgment steps, write reliability tests, and contribute to full-stack development and deployment. Work directly with stakeholders and learn relevant patent and intellectual-property domains.