Senior AI Engineer

<div class="content-intro"><h2 data-pm-slice="1 1 []">About Crunchyroll</h2> <p>Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.</p> <p>Join our team, and help us shape the future of anime!</p></div><p data-pm-slice="1 1 []">Enterprise Technology is building the core AI-native engineering capabilities needed to improve how we design, build, test, and ship software. This role will help apply AI-assisted engineering across Enterprise Technology projects while maintaining strong quality, security, and production-readiness standards.</p> <p>You will build production software, direct AI coding agents, review AI-generated work, improve delivery practices, and help turn what works into reusable patterns for future Enterprise Technology initiatives.</p> <p>In the role of Staff AI Engineer, you will report to the VP, Enterprise Technology.&nbsp;We are considering applicants for the location of Dallas, Texas (on-site Tuesdays, Wednesdays, and Thursdays).</p> <h2><strong>What You’ll Do:</strong></h2> <ul> <li>Build and ship production software for Enterprise Technology initiatives, including services, APIs, data models, user interfaces, integrations, tests, and operational tooling.</li> <li>Direct AI coding agents by writing clear specs, acceptance criteria, implementation plans, and verification steps.</li> <li>Review and own AI-generated code, tests, pull requests, and migrations for correctness, security, maintainability, and production readiness.</li> <li>Help establish repeatable AI-assisted engineering practices for Enterprise Technology projects.</li> <li>Design and implement integration-heavy, data-intensive, and workflow-driven systems for enterprise applications and operational platforms.</li> <li>Apply and extend AI-assisted engineering tooling, including coding-agent workflows, repo access patterns, context setup, automated verification, and reusable delivery templates.</li> <li>Track practical delivery metrics such as cycle time, quality, rework, test coverage, cost, adoption, and operational health.</li> <li>Partner with Product, Security, business stakeholders, and Enterprise Technology teams to deliver secure, maintainable software.</li> <li>Improve testing, review, observability, documentation, and operational practices for AI-assisted delivery.</li> </ul> <h2><strong>About You:</strong></h2> <p data