Back to SearchSenior AI Software Engineer
Hybrid in Singapore: Singapore
AI Solution Engineering
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We are seeking a Senior AI Software Engineer to build agentic AI and machine learning solutions from proof of concept to production. You will design, develop and deploy AI products, partner with cross-functional teams and improve delivery through automation and reusable components. You bring strong software engineering fundamentals plus applied data science skills.
Responsibilities
- Lead development of machine learning, advanced analytics and AI solutions that solve business problems
- Design and deliver AI products, including agentic AI applications for real use cases
- Build and operate AI agents and supporting services from proof of concept through production
- Develop Front-end and back-end software components aligned to cloud and data architecture standards
- Improve engineering workflows through automation, reusable components and tooling
- Test solutions using functional and performance techniques to meet quality targets
- Partner with teams to define cloud-based application and agent architecture, design and implementation
- Translate business requirements into technical designs using Agile delivery methods
Requirements
- Proven experience building and deploying AI, machine learning or data science solutions in production environments
- Hands-on experience with agentic AI frameworks and patterns, including skills, harnesses and model context protocols (MCPs)
- Strong software engineering fundamentals, including web application development and API design
- Cloud platform experience (for example, Amazon Web Services (AWS), Microsoft Azure or Google Cloud Platform (GCP))
- Database knowledge, including data modeling, implementation and performance considerations
- Testing capability, including functional, integration and performance testing approaches
- Agile delivery experience, including iteration planning, delivery and continuous improvement
- Clear communication with the ability to explain technical tradeoffs to diverse stakeholders
Nice to have
- Experience with AI and workflow platforms such as Databricks, Snowflake, Dataiku, n8n, Northflank or Microsoft Power Automate
- Containerization and orchestration exposure, such as Docker and Kubernetes (K8s)
- Experience with automated build, test and deployment pipelines, such as CI/CD practices and tooling