AI Product Engineer

• Bachelor's degree in Computer Science, Computer Engineering, a relevant 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.
• 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-off s to technical and non-technical stakeholders.

• 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 influencing product roadmaps by translating user feedback into actionable engineering requirements.
• Demonstrated experience using AI-assisted development or LLM-based systems to improve engineering velocity or redesign operational workflows, while independently reviewing and validating the resulting work.
• Experience contributing to shared codebases using 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.

End-to-end product engineering: experience independently designing, building, testing, launching, and operating production software involving APIs, backend services, data systems, or full-stack products.

Product and user judgment: ability to understand the “why” behind a request and translate ambiguous needs into a scoped technical approach.

Clear written and verbal communication, including explaining technical trade-offs to technical and non-technical stakeholders.