AI Product Engineer

MORGAN MCKINLEY PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Morgan McKinley Pte. Ltd. is collaborating with a leading multitechnology social media company to hire an Applied AI Product Engineer in Singapore.

The role centers on building internal tools and AI-powered workflows to support content, product, and research teams, emphasizing reliable design and scalable solutions. This six-month renewable contract involves collaborating with stakeholders, implementing end-to-end solutions, validating AI code, and documenting processes to enable teams to

Qualifications

• Bachelor's degree in CS or related field, or equivalent practical experience.
• 5+ years of software engineering, product engineering, ML engineering, or related experience.
• Experience building/integrating AI/ML-enabled products or evaluation systems.
• Proficiency in Python, JavaScript/TypeScript, Java, PHP/Hack, or C++, with API/backend experience.
• Strong production engineering practices: testing, observability, version control, and code reviews.

Responsibilities

• Collaborate with stakeholders to understand problems, define outcomes, and constraints.
• Design and build end-to-end internal tools and data workflows.
• Transform prototypes into scalable, reliable products with best practices.
• Develop evaluation frameworks for AI-powered workflows and validate code.
• Measure adoption, solution quality, and time savings for continuous improvement.
• Create documentation and onboarding resources for users and engineers.
• Manage multiple technical workstreams balancing impact and resources.

Skills

Communication skills

Product judgment

Problem solving

Independence

Education

Bachelor's degree in Computer Science or related field

Tools

Python

JavaScript/TypeScript

Java

C++

APIs & Backend

Job description

Our client is a leading Multitechnology social media company. As an Applied AI Product Engineer, you will build internal products and integrations that help content, product, and research teams design, evaluate, and launch AI-powered experiences. This is a 06 month [Renewable] Contract.

Job Responsibilities

• Collaborate with technical and non-technical stakeholders to understand business problems, define desired outcomes, and identify constraints before selecting appropriate solutions.
• Design and build end-to-end internal tools, integrations, and data workflows that improve operational efficiency and user experience.
• Transform prototypes and one-off solutions into scalable, reliable, and reusable products using production engineering best practices, including testing, observability, error handling, and resilience.
• Develop evaluation frameworks and feedback loops for AI-powered workflows, leveraging AI coding tools responsibly and validating all generated code.
• Measure product adoption, solution quality, time savings, and reductions in manual support to drive continuous improvement.
• Create clear documentation and onboarding resources that enable users and engineers to operate and maintain solutions independently.
• Manage and prioritize multiple technical workstreams, balancing business impact, technical complexity, and available resources.

Job Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience, with more than 5 years of experience in software engineering, product engineering, ML engineering, or technical solutions development.
• Proven ability to independently own technical products from problem definition and solution design through implementation, launch, and continuous improvement, working effectively with ambiguous requirements
• Experience building or integrating AI/ML-enabled products, evaluation systems, or agentic workflows.
• Proficiency in one or more programming languages, such as Python, JavaScript/TypeScript, Java, PHP/Hack, or C++, with experience building APIs, backend services, data workflows, or full-stack applications.
• Strong understanding of production engineering practices, including automated testing, observability, debugging, error handling, version control, code reviews, and reliable system design.
• Experience leveraging data, metrics, AI/ML technologies, and AI-assisted development tools to improve product quality and engineering efficiency, with strong communication skills, product judgment, and a commitment to responsible AI practices.