Manager, Artificial Intelligence Office (1-yr contract)(8464)

National University Health System; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading healthcare institution is seeking a skilled Software Engineer to join the LLM Team. The role involves developing LLM solutions, collaborating with IT teams, and ensuring efficient tech frameworks. Candidates should possess extensive experience in tech delivery, full-stack development, and cloud technologies like AWS and Azure. Strong leadership and communication skills are essential, along with a background in Machine Learning and Data Visualization.

Qualifications

• Minimum of 5 years of experience in tech delivery.
• At least 4 years of experience as a full-stack engineer.
• Must have experience working with LLM technologies and on Machine Learning projects.

Responsibilities

• Collaborating with the LLM lead and team members to ensure high standards in technical delivery.
• Guiding junior software engineers and troubleshooting problems.
• Contributing to projects, committing code, and performing code reviews.

Skills

DevOps

C#

Java

Python

Docker

Kubernetes

React

Angular

Data Visualization

Machine Learning

Education

Bachelor of Science in Computer Science

Tools

AWS

Azure

Docker

Kubernetes

Grafana

Tableau

PowerBI

Job description

Overview

Reporting to the GCTO-Solutions lead, you will develop multiple LLM solutions for the LLM Team. You will work closely with your team lead to implement technical priorities and standards for developing and managing technology solutions within the LLM team. The role also involves ensuring the adequacy and effectiveness of NUHS(GCTO) tech frameworks and stacks to deliver production-ready solutions/services that can be scaled within the NUHS cluster and beyond.

Job Responsibilities

You will be responsible for:

• Working as a Software Engineer (SWE) in the LLM Team under Solutions, collaborating with the LLM lead and team members to ensure high standards in technical delivery.

• Supporting all production-related activities for LLM.

• Spending approximately 90% of your time on development work, contributing to projects, committing code, and performing code reviews.

• Using the remaining 10% of your time to coordinate with the team lead and colleagues on relevant duties.

• Collaborating with healthcare IT teams to integrate cloud-based solutions with existing on-premises systems and electronic health records (EHRs).

• Assisting in architectural diagramming and SRB clearance for cloud solutions.

• Guiding junior software engineers and troubleshooting problems to achieve project goals.

• Helping organize local AI/Tech conferences and showcasing NUHS AI/Tech capabilities to attract talent.

Requirements

• A Bachelor of Science degree in Computer Science or a related field such as Math, Physics, or Engineering from a recognized university.

• Minimum of 5 years of experience in tech delivery.

• Experience working with and coordinating multiple development teams.

• At least 2 years of experience working with DevOps teams on AWS, Azure, Alibaba Cloud, or Google Cloud.

• Experience with on-premises teams is a plus.

• 2 years of experience with Docker and Kubernetes is desirable.

• At least 4 years of experience as a full-stack engineer.

• At least 4 years of experience with C#/Java and 2 years with Python.

• Experience with front-end technologies like React and Angular for at least 4 years.

• Mobile development experience is a plus.

• Experience with Data Visualization tools such as Grafana, Tableau, or PowerBI.

• Familiarity with both Waterfall and Agile project management methodologies is a plus.

• Experience with event-driven/messaging systems like Kafka and RabbitMQ for at least one year.

• Must have experience working with LLM technologies and on Machine Learning projects.

• Healthcare experience is a bonus, especially in Data Visualization, Machine Learning, LLMs, and full-stack cloud application development.

• Strong written and verbal English communication skills for effective technical interaction.