Applied AI Product Engineer

Role overview Turn promising AI ideas into working products, prototypes, and internal tools, often starting from an open-ended problem rather than a detailed specification. You’ll build across the stack, use language models and coding agents as core development tools, and test solutions with users to determine what can create meaningful value in complex content workflows.

Responsibilities - Investigate difficult or costly technical problems and build proof-of-concept solutions that test what is possible. - Create end-to-end prototypes and applications spanning user interfaces, backend services, data, integrations, and deployment. - Build language model systems using methods such as structured generation, tool use, retrieval, agents, model routing, evaluation, and human review. - Combine models, APIs, databases, open-source software, and existing services to support content, metadata, search, and automation workflows. - Put prototypes in front of users and stakeholders, then adapt them based on observed results. - Judge when rapid iteration is appropriate and when security, permissions, reliability, cost, or maintainability need more engineering; explain system behavior and production considerations.

Requirements - A degree in computer science, engineering, or a related technical field, or equivalent practical experience shipping software. - Strong full-stack skills and the ability to build across frontend, backend, data, and deployment. - Hands-on experience building applications with commercial or open-source language models, including model APIs, context design, tool calling, or agent workflows. - A portfolio of working products, prototypes, repositories, open-source work, or hackathon builds showing technical depth and execution. - Ability to use AI-generated code effectively while independently reviewing architecture, debugging, and identifying security or quality risks. - Resourcefulness with incomplete requirements, sound product judgment, and clear communication with technical and business partners.

Nice to have - A habit of building side projects and experimenting independently is valued.