AI Product Engineer (Big Tech)

Morgan McKinley; Singapore; On-site; SGD 78,000 - 134,000; Part time

Job summary

Morgan McKinley seeks an Applied AI Product Engineer in Singapore to build internal products, integrations, and self-service tooling for content, product, and research teams. You will own end-to-end workstreams, turning manual workflows into scalable capabilities.

You will design AI-powered workflows, implement robust testing, and partner with stakeholders to define requirements and onboarding paths. This role emphasizes responsible AI practices and reliable delivery.

Qualifications

• Bachelor’s degree or equivalent practical experience in a technical field.
• 6+ years building production software across software/ML/product engineering roles.
• Proven ability to lead ambiguous technical projects from scoping to iteration.
• Strong background in APIs, backend services, data workflows, or full‑stack products.
• Experience with unit/integration testing, observability, logging, and resilient error handling.
• Ability to define data‑driven metrics and communicate trade‑offs to non‑technical partners.

Responsibilities

• Design, code, test, and operate end-to-end internal products, integrations, and data workflows from inception to post-launch iteration.
• Identify repeated technical support requests and convert them into self-service tools.
• Design evaluation and feedback systems to measure AI workflow output quality, safety, and performance.
• Apply robust software engineering practices including automated testing and reliable monitoring.
• Collaborate with technical and non-technical stakeholders to clarify problems and onboarding paths.
• Lead multiple technical workstreams, balancing speed and complexity while tracking adoption and impact.
• Leverage AI coding tools to boost velocity while ensuring code quality and validation.

Skills

APIs

Backend services

Data workflows

Full-stack familiarity

Education

Bachelor’s degree in Computer Science

Equivalent practical experience

Tools

CI/CD pipelines

Observability tools

Job description

Job Type: 6-Month Contract (Possibility to extend or convert to permanent)

About the Role

We are seeking a hands-on Applied AI Product Engineer to build internal products, integrations, and self-service platform tools that enable our content, product, and research teams to design, evaluate, and launch cutting-edge AI experiences.

In this role, you will bridge the gap between ambiguous user problems and production-ready engineering solutions. You won't just write code; you will own end-to-end workstreams—turning manual operational workflows, repeated support requests, and quick prototypes into scalable, reliable, and reusable technical capabilities.

What You’ll Do

• Design, code, test, and operate end-to-end internal products, integrations, and data workflows from inception to post-launch iteration.
• Identify repeated technical support requests and manual internal workflows, transforming them into reliable self-service tools.
• Design evaluation, testing, and feedback systems for AI-powered workflows to measure output quality, safety, and performance.
• Apply robust software engineering practices, including automated testing, observability, actionable error monitoring, and safe failure handling.
• Partner closely with both technical and non-technical stakeholders to clarify problem statements, define requirements, and build intuitive developer/user onboarding paths.
• Own and prioritize multiple technical workstreams, balancing trade-offs between speed and complexity while tracking adoption, quality, and time saved.
• Utilize modern AI coding tools intentionally to boost velocity, while rigorously reviewing and validating all generated code.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
• 6+ years of hands-on experience building production software across software engineering, product engineering, ML engineering, or technical solutions engineering.
• Demonstrated track record of independently leading ambiguous technical projects through scoping, system design, implementation, launch, and iteration.
• Strong background in building or integrating APIs, backend services, data workflows, or full-stack products, with proven skills in debugging complex integration issues.
• Proven practice with unit/integration testing, observability, log monitoring, and resilient error handling.
• Experience defining data-driven metrics to evaluate product outcomes and clearly articulating technical trade-offs to non-technical partners.

Preferred Qualifications

• Experience building or integrating AI/ML-enabled software, agentic workflows, or LLM evaluation frameworks.
• Prior success building internal developer platforms, developer tooling, or enterprise self-service capabilities.
• Strong product judgment with experience translating raw user feedback into actionable technical roadmaps.
• Hands-on experience using AI-assisted development tools to redesign operational workflows and accelerate engineering output.
• Active experience in collaborative engineering practices: shared codebases, rigorous code reviews, automated CI/CD pipelines, and clean technical documentation.
• Understanding of Responsible AI frameworks, including risk assessment, bias mitigation, and accuracy reviews.