Applied AI Product Engineer

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