Lead Research Software Engineer: AI for Clinical Data

RGIT Australia; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Cambridge CARES in Singapore is seeking a Lead Research Software Engineer to develop a high-volume clinical data database and reproducible data pipelines for the BloodCounts! AI4S project.

You will build robust backend infrastructure, ensure data quality, and enable scalable AI research across multi-modal datasets. You will lead deployment of federated learning infrastructure, work with researchers and partners across academia and industry, and mentor team members while upholding strict security

Qualifications

• Substantial software engineering experience in a research, data-intensive or clinical context (5–10 years)
• Expert proficiency in Python with strong SQL
• Strong experience with CI/CD and version control
• Experience designing and operating distributed systems and federated learning infrastructures
• Security-by-design across SDLC and confidential data handling
• Experience with containerisation (Docker) and orchestrators (Kubernetes)
• Experience with high-volume databases (PostgreSQL, analytical stores) and data formats (Parquet, HDF5)
• Experience with data pipelines and workflow tools (Airflow, Dagster, Snakemake)
• Strong ability to lead and mentor teams and communicate with clinical/IT stakeholders

Responsibilities

• Develop high-volume clinical data storage and reproducible data curation pipelines
• Deliver enterprise-grade backend infrastructure and data pipelines for clinical studies
• Lead deployment of federated learning infrastructure and related tooling
• Collaborate with multi-disciplinary teams across universities and partners
• Set technical direction for a team and mentor researchers in software engineering

Job description

Cambridge CARES in Singapore is seeking a Lead Research Software Engineer to develop a high-volume clinical data database and reproducible data pipelines for the BloodCounts! AI4S project.

You will build robust backend infrastructure, ensure data quality, and enable scalable AI research across multi-modal datasets. You will lead deployment of federated learning infrastructure, work with researchers and partners across academia and industry, and mentor team members while upholding strict security