Data & AI Full-Stack Engineer

CAPGEMINI SINGAPORE PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Capgemini Singapore Pte. Ltd. is seeking a motivated Full-stack Engineer with an interest in data engineering and AI/ML to join our team. You will contribute to developing and maintaining applications while learning to integrate AI/ML components and manage data pipelines.

The role emphasizes backend development, cloud technologies, DevOps automation, and application security, with opportunities to work across data pipelines and high-performance services.

Qualifications

• Bachelor's degree required in CS/SE or related field.
• Proficiency in Python and SQL required.
• Experience with Git and collaborative workflows.
• Experience with CI/CD pipelines.
• Experience with SQL and NoSQL databases.
• Knowledge of RESTful APIs/web services.
• Understanding of backend scalability strategies.
• Familiarity with frontend frameworks (React/Angular/Vue) or backend (Django/Node.js/Flask).

Responsibilities

• Own end-to-end application development, integrating frontend, backend and cloud infra.
• Tune and automate CI/CD deployment pipelines for production releases.
• Collaborate with data engineers to implement data pipelines in production.
• Develop high-performance backend services and APIs with security and observability.
• Explore AI/ML opportunities to enhance data pipelines.
• Write clean, maintainable code and adhere to best practices.
• Participate in code reviews and maintain technical docs.
• Support testing and debugging across environments.

Skills

Python

SQL

Git

CI/CD pipelines

RESTful APIs

Web services

Backend scalability

Frontend frameworks

Education

Bachelor's degree in Computer Science/Software Engineering

Tools

Docker

Kubernetes

Terraform

Job description

Capgemini Singapore Pte. Ltd. is seeking a motivated Full-stack Engineer with an interest in data engineering and AI/ML to join our team. You will contribute to developing and maintaining applications while learning to integrate AI/ML components and manage data pipelines.

The role emphasizes backend development, cloud technologies, DevOps automation, and application security, with opportunities to work across data pipelines and high-performance services.