Engineering Manager

Woven by Toyota is hiring an Engineering Manager for its Generative AI Engineering team within the Developer Productivity function, which builds tools, platforms and workflows that help engineering teams at Woven and the broader Toyota organization move faster while keeping safety, security and quality top priorities. The Generative AI Engineering team builds enterprise-grade AI platforms and developer-facing AI capabilities: secure access to large language models, AI gateways, internal AI tooling, model-usage governance, identity-aware authorization, cost controls, observability, and integrations with engineering systems. As EM you would define and lead the technical direction, manage and grow the team, break down ambiguous problems into technical plans, own delivery (prioritization, planning, dependency management, risk communication), lead building of secure/reliable/observable AI platform services, define and track adoption/usage/quality/cost metrics, manage technical debt and architectural consistency, and stay close to implementation. You should understand developer productivity, platform engineering and enterprise generative AI, and turn that into a clear vision. Reports to the Head of Developer Experience and Generative AI; hybrid with at least 3 office days per week. Full-time, based in Tokyo.

English communication sufficient to explain technical trade-offs, risks, and priorities to technical and non-technical stakeholders is required; Japanese communication is preferred.

Applicants need a relevant bachelor’s or master’s degree, or equivalent practical experience, and at least seven years of professional software engineering, including at least three years managing or leading a technical team. Required experience includes delivery of complex platforms or tools, managing and developing engineers, CI/CD, automated testing, infrastructure as code, cloud/container deployments and production systems using LLM APIs or generative AI. Candidates also need knowledge of production AI security, access control, observability, costs, evaluation and reliability, and strong architecture and operations fundamentals.