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