• Partner with technical and non-technical users to understand the problem, desired outcome and constraints before selecting a sol
• Build end-to-end internal products, integrations and data workflows
• Turn prototypes and one-off solutions into reliable, reusable capabilities

Overview

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. You will work across the product lifecycle, from understanding ambiguous user problems and defining a technical approach to implementation, launch and iteration.

This is a hands-on engineering role. Most of your time will be spent designing, coding, testing and operating solutions, with enough internal user interaction to make sure the right problems are being solved. A core part of the role is turning repeated technical support and manual workflows into reliable self-service tools. The work spans AI product evaluation tooling, data and analytics workflows, and new applied-AI prototypes.

Key Responsibilities

• Partner with technical and non-technical users to understand the problem, desired outcome and constraints before selecting a solution
• Build end-to-end internal products, integrations and data workflows
• Turn prototypes and one-off solutions into reliable, reusable capabilities
• Design evaluation and feedback loops for AI-powered workflows
• Apply production engineering practices, including testing, observability, actionable errors and safe failure handling
• Use AI coding tools thoughtfully, reviewing and validating all generated work
• Measure adoption, quality, time saved and reduction in manual support
• Create documentation and onboarding paths so users and engineers can operate independently
• Own and prioritise several technical workstreams, making clear trade-offs based on impact and complexity

What a Typical Day Looks Like

• Clarifying the underlying user problem and success criteria
• Designing and building APIs, internal tools, data workflows and product integrations
• Testing, debugging, instrumenting and documenting what you build
• Reviewing quality, adoption and workflow metrics
• Working with internal content, product and cross-functional teams to gather feedback and iterate

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering or a related technical field, or equivalent practical experience
• 6+ years of experience building production software in software engineering, product engineering, ML engineering or a hands-on technical solutions role
• Experience independently owning scoped technical products from an ambiguous problem through design, implementation, launch and iteration
• Proficiency in one or more general-purpose programming languages, such as Python, JavaScript/TypeScript, Java, PHP/Hack or C++
• Experience building or integrating APIs, backend services, data workflows or full-stack products, including debugging complex integration issues
• Experience applying production engineering practices such as automated testing, observability, actionable errors and safe failure handling
• Experience using data and metrics to evaluate outcomes, and communicating technical concepts and trade-offs to technical and non-technical stakeholders

Preferred Qualifications

• Experience building or integrating AI/ML-enabled products, evaluation systems or agentic workflows
• Experience building internal tools, developer platforms or reusable self-service capabilities
• Strong product judgment, or experience shaping product roadmaps by turning user feedback into engineering requirements
• Experience using AI-assisted development or LLM-based systems to improve engineering velocity or redesign workflows, while independently reviewing and validating the results
• Experience contributing to shared codebases with version control, code review, automated testing and documented engineering practices
• Experience applying responsible AI practices such as risk assessment, bias mitigation, and quality and accuracy reviews

We regret to inform that only shortlisted candidates will be notified.

EA Reg No: R26162461, Nicki Thng
Allegis Group Singapore Pte Ltd, Company Reg No. 200909448N, EA License No. 10C4544