About Crunchyroll 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.

Join our team, and help us shape the future of anime!

About The Role

In the role of Principal AI Engineer for Concepts Lab , you will report to the VP of the Concepts Lab. We are considering applicants for the location of Los Angeles, CA (onsite). As the Principal AI Engineer for Concepts Lab , you will be the technical anchor for everything AI in the lab: designing and building the agentic delivery tooling, evaluation harnesses, and paved paths that let cross-functional pods take ideas from concept to production in days instead of months.

This is a hybrid technical and enablement role. You will move fluidly between hands-on agent and platform development, instrumenting and measuring whether the system is actually working, and partnering with stakeholders across the company to roll those capabilities out. Success in your first year looks like a Concepts Lab where the cross-functional pod model has been stress-tested with real evidence, and where we can point to specific KPIs and say with confidence whether agentic delivery is making us faster and better, or whether we need to course-correct.

Core Areas of Responsibility Own the design and evolution of the lab’s agentic delivery system, including the agent harness, CLI and skill interfaces, workflow orchestration, isolation, evaluation, and observability layers that let agents safely read, write, refactor, and test code across our repos. Own the measurement layer that tells us whether agentic delivery is working. You will define and instrument the KPIs we will judge this program by, including cycle time (idea to prototype, decision to production), quality and rework rates, integration cost, eval pass rates, cost per cycle, pod throughput, adoption, and direction-stability signals.

You will build the dashboards and learning reports that turn the lab’s 2-week sprints into evidence executives can act on, and you will be honest when the numbers say something is not working. Lead the integration work that makes agents effective in our environment, including context engineering, repo and tool access patterns, MCP servers, and the connective tissue between agents and the systems they need to reason about (codebases, docs, ownership, incidents, runtime). Drive enablement and adoption across Product, Design, and Engineering.

You will run the rollouts that take the agentic stack from Concepts Lab into pilot teams and beyond: onboarding cross-functional pods, codifying paved paths and best-practice playbooks, embedding alongside teams during their first cycles, and using the feedback to harden the platform. You will be the person whose job it is to make the tooling actually get used, not just exist. Set the technical bar for the lab’s AI work, including design reviews, code quality, eval coverage, observability, cost management, and security practices, and mentor the engineers and contractors who collaborate with us.

Be the opinionated voice on how cross-functional pods should be designed and how agentic systems scale inside a large engineering organization. You will help leadership think clearly about pod composition, human touchpoints, where to keep humans in the loop and where to take them out, how to roll out team by team without breaking what works, and how to avoid the common failure modes (review overload, shadow product teams, prototypes that become unowned production systems). You will bring a strong point of view, defend it with evidence, and update it when the data says you were wrong.