Senior AI Engineer: Build AI Apps & Scale Solutions

RISKDATA CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RISKDATA CONSULTING PTE. LTD. in Singapore seeks a senior AI/ML engineer to lead development of analytics, machine learning, and AI-driven solutions for business challenges. You will design AI products, build production-ready agents and applications, and shape cloud-based architecture.

You will collaborate across teams, apply Agile methods, and drive end-to-end lifecycle from roadmap to deployment, with emphasis on standardised engineering practices and scalable data solutions.

Qualifications

• Experience in Agentic AI engineering, web app development, or data science.
• Hands-on with AI techniques and practical AI frameworks.
• Familiar with AI tools, frameworks, and open-source libraries.
• Knowledge of database design and cloud services.
• Experience with Agile delivery and cloud platforms.
• Strong problem solving and stakeholder management skills.

Responsibilities

• Lead development of analytics, ML, and AI-driven solutions for business challenges.
• Design, develop, and implement AI products and agent-based applications.
• Build and productionize AI-powered agents and apps.
• Develop software across frontend/backend with cloud data architecture.
• Improve workflows with automation and reusable components.
• Collaborate with teams to ensure quality and timely delivery.

Skills

Agentic AI

Web development

Data science

Agile

Cloud computing

AI frameworks

Testing & QA

DevOps

Containerization

Cross-functional

Education

Bachelor’s degree or higher

Tools

n8n

Dataiku

Databricks

Snowflake

Power Automate

Job description

RISKDATA CONSULTING PTE. LTD. in Singapore seeks a senior AI/ML engineer to lead development of analytics, machine learning, and AI-driven solutions for business challenges. You will design AI products, build production-ready agents and applications, and shape cloud-based architecture.

You will collaborate across teams, apply Agile methods, and drive end-to-end lifecycle from roadmap to deployment, with emphasis on standardised engineering practices and scalable data solutions.