Senior Software Engineer – AI & Data Science

Our client is a growing Singapore-based organisation driving AI and data science initiatives across its digital products and services. They're looking for an experienced engineer to help take AI-powered solutions from proof-of-concept through to production.

What You'll Do

Lead the development of advanced analytics, machine learning, and AI-driven solutions that generate actionable business insights.

Design, build, and deploy AI products, including applications built on Agentic AI frameworks, for real business use cases.

Build and maintain AI-powered agents and applications, taking them from proof-of-concept to production.

Design and implement software solutions across frontend and backend systems, applying cloud application and data architecture principles.

Improve engineering workflows through automation, reusable components, and standardised practices.

Conduct functional and performance testing to ensure high-quality solution delivery.

Partner with cross-functional and technology teams on solution architecture, requirements, and Agile delivery.

Support the end-to-end product lifecycle, from roadmap planning through deployment and continuous improvement.

Core Key Skills

Relevant experience in Agentic AI engineering, web application development, data science, or a related discipline.

Hands-on experience developing and implementing AI skills, harnesses, MCPs, or other Agentic AI frameworks in production applications.

Familiarity with AI tools, frameworks, and open-source libraries.

Knowledge of database design, implementation, and management.

Familiarity with Agile delivery methodologies and cloud computing platforms.

Strong analytical and problem-solving skills, able to translate business problems into technical solutions.

Excellent communication and stakeholder management skills across multidisciplinary teams.

Nice to Have

Experience with commercial AI, workflow, or data platforms such as n8n, Dataiku, Databricks, or Snowflake.

Familiarity with containerisation, orchestration, and automated build/test/deployment pipelines.

A track record of continuous learning and staying current with AI and software engineering trends.