Senior AI Engineer

dadaconsultants pte. ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

dadaconsultants pte. ltd. is partnering with a fast-growing AI technology company to hire a Senior AI Engineer. The role focuses on designing and delivering production-grade AI solutions for enterprise clients, turning AI research into scalable software systems.

You will design robust AI platforms, build production-ready services, and deploy ML solutions across cloud and hybrid environments while promoting engineering best practices across the team.

Qualifications

• Bachelor's or Master's degree in CS/AI/Software Engineering or related field
• 4+ years of experience building and deploying production software or AI/ML systems
• Strong software engineering fundamentals with emphasis on system architecture and backend development
• Hands-on experience with cloud platforms (AWS, Azure, or GCP)
• Experience with Docker, Kubernetes, CI/CD, Infrastructure as Code, and modern deployment practices
• Strong Python programming skills
• Experience with SQL and NoSQL databases
• Experience designing RESTful APIs and microservices
• Familiarity with AI model deployment, orchestration frameworks (Airflow, Ray, Prefect), or MLOps workflows is advantageous
• Excellent problem-solving skills and collaborative working style

Responsibilities

• Design and develop modular, scalable, and production-ready AI applications and backend services
• Build reusable software components and system architectures supporting complex enterprise use cases
• Develop AI-driven services and integrate ML models into production systems
• Design and implement APIs, microservices, and distributed system architectures
• Deploy and maintain AI applications across cloud and hybrid environments using DevOps and MLOps practices
• Contribute to engineering standards, code quality, testing, and technical design reviews
• Collaborate with AI researchers, software engineers, and product teams to deliver reliable AI solutions

Skills

Python programming

Backend development

System architecture

Problem solving

Team collaboration

Education

Bachelor's or Master's degree in CS/AI/Software Engineering

Tools

Docker

Kubernetes

CI/CD

Infrastructure as Code

Airflow

Ray

Prefect

Job description

About the Role

We are partnering with a fast-growing AI technology company to hire a Senior AI Engineer to design and deliver production-grade AI solutions for enterprise customers.

This role is ideal for engineers who enjoy turning AI research into scalable software systems. You'll work on designing robust AI platforms, building production-ready services, and deploying machine learning solutions in cloud and hybrid environments while contributing to engineering best practices across the team.

Responsibilities

• Design and develop modular, scalable, and production-ready AI applications and backend services.
• Build reusable software components and system architectures that support complex enterprise use cases.
• Develop AI-driven services and integrate machine learning models into production systems.
• Design and implement APIs, microservices, and distributed system architectures.
• Deploy and maintain AI applications across cloud and hybrid environments using modern DevOps and MLOps practices.
• Contribute to engineering standards, code quality, testing, and technical design reviews.
• Collaborate closely with AI researchers, software engineers, and product teams to deliver reliable AI solutions.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related discipline.
• 4+ years of experience building and deploying production software or AI/ML systems.
• Strong software engineering fundamentals with experience in system architecture and backend development.
• Hands‑on experience with cloud platforms (AWS, Azure, or GCP).
• Experience with Docker, Kubernetes, CI/CD, Infrastructure as Code, and modern deployment practices.
• Strong Python programming skills.
• Experience with SQL and NoSQL databases.
• Experience designing RESTful APIs and microservices.
• Familiarity with AI model deployment, orchestration frameworks (e.g. Airflow, Ray, Prefect), or MLOps workflows is advantageous.
• Excellent problem‑solving skills and the ability to work in a collaborative engineering environment.