NUS Enterprise

Entrepreneurial hub accelerating startups and commercialization

Applied AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours

Full-timeSingaporeNo salary listed

About the Job

Requirements

At least 3 years of hands-on experience in software engineering, data engineering, system integration, or automation development; an AI-specific job title is not required.
Strong Python or TypeScript/Node skills, with experience building and consuming REST and/or GraphQL APIs, authentication using OAuth or service accounts, and SQL/Postgres.
Have shipped at least one feature, integration, or workflow that calls an LLM API; classification, extraction, agents, and RAG count, and no particular framework is expected.
Good testing habits, including integration or contract testing, and documentation another person can follow.
Daily use of AI-assisted coding tools such as Claude Code, Cursor, GitHub Copilot, or similar.
Comfort working with non-technical users and turning a vague pain point into working software.
Degree or diploma in a technical discipline, or equivalent practical experience.

Responsibilities

Build, test, ship, and maintain connectors and AI-assisted workflows end to end for real users.
Create a consistent integration backbone with a shared authentication pattern, schema contract, contract tests, and reusable documentation.
Build an agent harness with deterministic guardrails, including a tool server for agents and automations to write to shared boards with allow-listed boards and columns, logged writes, and no deletes.
Build an intake agent that converts inbound email into a structured, classified ticket and use an evaluation set to measure its accuracy.
Build a milestone watchdog that reads award milestones from source systems, identifies due or at-risk items, and writes a status flag for the team.
Prepare a demonstrable solution and documentation for handoff.
Run requirements and acceptance testing directly with users and adapt the work based on what is learned.
Work directly with the technical lead and present work to senior leadership.

Desired Qualifications

Familiarity with writing MCP servers from scratch or other tool-calling backends.
Familiarity with Monday.com (GraphQL), n8n, Google Workspace, or Slack integrations.
Familiarity with writing and optimizing agentic skills.
Experience with evaluation sets or prompt regression checks for LLM features.
Experience with embeddings, vector databases such as pgvector, and RAG.
Experience with Google Cloud.
Comfort reading and working in English and Chinese.

(30378) Applied AI Engineer, NUSX Labs

NUSX · Singapore, Singapore · Contract · Posted 2026-10-27

Workplace: on_site

Department: AI & Systems (ETP)

Description

ABOUT NUSX LABS
NUSX Labs is the AI team at NUSX. Behind every NUS invention that reaches the market and every research grant that funds a lab sits a long trail of paperwork. We turn that trail into software people actually use, so research gets out of the lab faster.

Every year, thousands of invention disclosures, patent filings, agreements and grant milestones move through inboxes, spreadsheets and half a dozen systems that were never designed to talk to each other. People re-key the same facts, chase status by hand, and hear about problems late. We are building the layer that connects those systems, with AI doing the clerical reading and sorting on top of it, so the people who move NUS research into the world spend their time on the work that needs a person.

THE ROLE
You will be a hands-on engineer at NUSX Labs. You own connectors and AI-assisted workflows end to end: build them, test them, ship them to real users, and keep them running.

What you'll ship in your first six months:

An integration backbone. Every system plugs in the same way: one auth pattern, one schema contract, contract tests, and docs a new teammate can copy.
An agent harness with deterministic guardrails. A tool server that lets agents and automations write to shared boards, with the limits enforced in code rather than the prompt: allow-listed boards and columns, every write logged, no deletes.
An intake agent. An inbound email arrives, and a structured, classified ticket comes out the other side, backed by an evaluation set so we know exactly how often it gets it right.
A milestone watchdog. It reads award milestones from the source systems, spots what is due or at risk before anyone has to chase, and writes a status flag back for the team.
A demo you can stand behind in front of senior leadership, with the documentation to hand it on.

Why you'll like it here

You own it end to end. From day one, you build, test, ship and run each connector or workflow yourself.
Your work ships. It goes to real users, not an internal tool, not a shiny demo.
Close to users. You run requirements and acceptance testing directly with the people who use the result, and you change the work based on what you learn.
Close to the decisions. You work directly with the technical lead and present your work to senior leadership.
AI-native by default. Claude Code or an equivalent is part of every working day, and we expect you to be fast and surgical with it.

Requirements

WHAT YOU'LL NEED

At least 3 years of hands-on experience in software engineering, data engineering, system integration or automation development. An AI-specific job title is not required.
Strong Python or TypeScript/Node, with experience building and consuming REST and/or GraphQL APIs, authentication (OAuth, service accounts) and SQL/Postgres.
You have shipped at least one feature, integration or workflow that calls an LLM API. Classification, extraction, agents and RAG all count, and no particular framework is expected.
Good testing habits, including integration or contract testing, and documentation another person can follow.
Daily use of AI-assisted coding tools (Claude Code, Cursor, GitHub Copilot or similar).
Comfort working with non-technical users and turning a vague pain point into working software.
Degree or diploma in a technical discipline, or equivalent practical experience.

NICE TO HAVE

Familiar with writing MCP servers from scratch or other tool-calling backends.
Familiar with one or more of: Monday.com (GraphQL), n8n, Google Workspace or Slack integrations.
Familiar with agentic skill writing, optimisation.
Evaluation sets or prompt regression checks for LLM features.
Embeddings, vector databases (pgvector or similar) and RAG.
Experience with Google Cloud.
Comfortable reading and working in English and Chinese.

Please be informed that only shortlisted candidates will be notified.

More Information

Job Type: 2-Year Contract

Location: Kent Ridge Campus

Organisation: NUSX

Department: Administration

Job requisition ID: 30378

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About the Company

NUS Enterprise

Entrepreneurial hub accelerating startups and commercialization

NUS Enterprise supports and grows entrepreneurship at the National University of Singapore. It seeds ideas, sparks innovations, and scales ventures from campus into global companies by offering experiential learning, ecosystem building, technology translation and commercialisation, and strategic global partnerships. It has helped nearly 4,300 students and over 3,000 start-ups, including 10 unicorns, and aims to improve the lives of 1 billion people in the next decade by building a worldwide innovation network. Their approach combines education, mentorship, access to resources and markets, and collaborations to turn research and ideas into real-world impact.

Company size: Not listed
Company stage: Not listed
Total funding: $2.9M
Headquarters: Singapore, Singapore
Founded: 2001

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