Staff Product Engineer, Gizmo

• 8+ years of software engineering experience
• Strong expertise in TypeScript is preferred; however, we would also consider candidates with strong JavaScript experience
• Degree in Machine Learning, Artificial Intelligence, or a related quantitative discipline; alternatively, demonstrable hands-on experience evaluating AI models and prompts in a production environment
• Experience building and maintaining production systems
• Experience shipping user-facing product features
• Experience designing structured or agentic prompt workflows
• Ability to define and implement evaluation metrics for AI-driven features
• Clear communicator who can collaborate with technical and non-technical stakeholders
• Strong product instincts and a focus on impact

Desirable

• We’re hiring an experienced/staff-level Product Engineer (AI-focused) to build and scale the core intelligence behind Gizmo
• Reporting to the CEO and Co-Founder, you’ll work across our TypeScript codebase to ship AI-powered features used daily by thousands of students, including study material generation, quizzes, automated marking and content ingestion
• This is not an ML research role. It is a hands-on product engineering position focused on designing and improving production AI systems with real user impact
• If you want to build AI that sits at the heart of a product and see your work make a tangible difference at scale, this role offers genuine impact
• You will operate as a full product engineer, owning AI features end to end:
• Design and ship AI-driven user-facing features in our TypeScript stack
• Take ownership of AI features from idea through to production and iteration
• Collaborate closely with design and product to solve real learning problems with end to end AI solutions
• Write clean, maintainable, production-ready code
• Contribute to architectural decisions across backend and AI systems
• Improve the user experience around AI outputs, including feedback loops and refinement flows
• You will take responsibility for AI systems that are already live and used daily. These include:
• Study material content generation
• Quiz question generation
• Automated marking and feedback
• Structured content ingestion pipelines
• You will optimise production AI pipelines
• Design and iterate on prompts, including agentic prompt engineering and multi-step workflows
• Build structured model pipelines rather than simple single-call integrations
• Integrate model improvements directly into our TypeScript backend
• Create novel AI-powered systems to solve new product challenges
• Prototype and productionise new model-driven capabilities
• Define what great looks like across different AI use cases
• Design internal evaluation frameworks
• Develop clear metrics for quality, correctness and usefulness
• Evaluate multi-step and agentic workflows for robustness
• Run structured experiments to drive systematic improvement
• Build internal tooling to support iteration and experimentation
• Monitor model behaviour and system health
• Handle API rate limits and third-party outages
• Improve resilience, retries and fallback logic
• Design robust model-calling infrastructure
• Ensure AI features remain stable and performant under scale