You will build internal AI-enabled products, tools, systems, and workflows that help our teams create, review, approve, manage, and ship game content more efficiently.
· Tools that turn creative direction into structured production workflows.
· AI-assisted content generation systems with human review and approval gates.
· Internal products that help designers, artists, product managers, and live operations teams produce and manage content.
· Data models, APIs, queues, orchestration layers, and UI surfaces that support repeatable workflows.
· Agentic workflows that break complex production tasks into reliable, reviewable steps.
· Systems that track inputs, generated outputs, approvals, revisions, quality checks, and production readiness.
· Workflow automation that reduces manual work while keeping creative and quality standards high.
You will own the quality of what the system produces, not just the plumbing that moves data around.
· Design, build, test, and maintain full stack applications that support AI-enabled game production workflows.
· Own features end to end, including data modeling, backend logic, API design, frontend implementation, deployment, and ongoing improvement.
· Build structured generation workflows that produce reliable, reviewable outputs from AI models.
· Create human-in-the-loop review systems so teams can steer, approve, reject, edit, and improve generated content.
· Translate ambiguous creative or operational goals into clear specifications, scoped plans, and production-ready systems.
· Build internal tools that improve speed, consistency, visibility, and quality across content production workflows.
· Partner with engineering, product, design, art, live operations, and leadership to understand workflow pain points and build practical solutions.
· Implement approval steps, audit trails, retries, staged processing, idempotency, and other patterns required for reliable production systems.
· Use AI coding agents and assistants as part of your daily workflow, while maintaining strong engineering judgment and code quality.
Review generated code, model outputs, workflow logic, and product behavior with a high bar for accuracy and usability.
Improve system reliability, observability, documentation, maintainability, and developer experience.
Contribute to a practical AI-first engineering culture focused on speed, quality, and measurable business impact.