(30378) Applied AI Engineer, NUSX Labs
Machine Learning EngineerData
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Quick Summary
Key Responsibilities
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.
Technical Tools
Machine Learning EngineerData
- 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.
- 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
~1 min read- 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
~1 min read- 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.
Job Type: 2-Year Contract
Location: Kent Ridge Campus
Organisation: NUSX
Department: Administration
Job requisition ID: 30378
Location & Eligibility
Where is the job
Singapore, Singapore
On-site at the office
About this job
- Posted
- Today
Listing Details
- Posted
- October 27, 2026
- First seen
- October 27, 2026
- Last seen
- October 27, 2026
Posting Health
- Days active
- -1
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- October 27, 2026
Signal breakdown
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