Engineering Manager, Generative AI Engineering

About Woven by Toyota Woven by Toyota contributes to Toyota's transformation into a mobility company once in a hundred years. Inspired by our history of continuing to invent "for someone other than ourselves," our mission is to expand the definition of mobility, extend the ways mobility contributes to society, and continue to challenge the common sense of mobility through innovation that thinks of people.

We operate around four main pillars: AD/ADAS (Automated Driving and Advanced Driver Assistance Systems) technology, Arene, a vehicle software production platform for SDV (Software Defined Vehicles), Woven City, a mobility test course, and Cloud & AI, the digital infrastructure that supports our collaborative foundation. Additionally, essential business functions support the implementation of these teams, working together toward the realization of a "zero accident society" and the "mass production of happiness."

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About the Team Software development in the automotive industry presents unique challenges. Developers must build, test, secure, and deploy software across cloud environments, mobile devices, embedded systems, and vehicles. There is also a need for modern AI-powered tools that are safe, governed, observable, and integrated with enterprise systems.

The Developer Productivity department builds the tools, platforms, and workflows that enable the engineering teams at Woven by Toyota and the entire Toyota Group to develop faster while prioritizing safety, security, and quality.

As part of this department, the Generative AI team builds enterprise-grade AI platforms and AI capabilities for developers. We focus on secure access to Large Language Models, AI gateways, internal AI tools, governance for model usage, identity-aware authorization, cost management, observability, and integration with engineering systems.

Requirements We are looking for an Engineering Manager to lead a high-impact Generative AI Engineering team that provides enterprise-grade AI platform capabilities for Developer Productivity. We expect experience in leading complex engineering projects and working closely with engineers and stakeholders to identify practical accelerators that improve the build, test, operation, and delivery of engineering teams.

We seek someone who places deep importance on customer value and takes the time to understand the actual problems engineers are trying to solve. You will clarify requirements, make appropriate technical decisions, facilitate consensus on software design, and lead the delivery of reliable platform capabilities that can be used across multiple teams.

We welcome those who can provide direction while remaining sufficiently involved in implementation details. You will define goals, clarify priorities, reduce unnecessary rework, and lead the team's roadmap to align with the overall strategy for Developer Experience and Generative AI. You will continuously increase the team's impact by utilizing metrics that measure adoption, usage, quality, reliability, and business value.

We are looking for someone who understands the latest technical trends in Developer Productivity, Platform Engineering, and enterprise-grade Generative AI, and can translate them into a clear and motivating vision for the team.

Reporting to the Head of Developer Experience and Generative AI, you will work closely with this position to assist in strategy formation, lead execution, and deliver highly safe, reliable, and useful AI capabilities at enterprise scale. This is a hybrid position requiring at least 3 days of office attendance per week.

Responsibilities

• Define and lead the technical direction for enterprise Generative AI platform capabilities within Developer Productivity.
• Manage and guide the Generative AI Engineering team in close collaboration with the Head of Developer Experience and Generative AI, engineers, product partners, security teams, identity teams, and internal stakeholders.
• Break down ambiguous, high-level challenges into clear, actionable technical plans, milestones, and deliverables for the team.
• Take responsibility for the delivery of team commitments, including prioritization, planning, dependency management, progress tracking, and communication of risks and trade-offs.
• Lead the construction of secure, reliable, observable, and maintainable AI platform services, including AI gateways, LLM providers, identity systems, developer tools, and integration with enterprise systems.
• Define and track metrics for the features provided by the team, such as adoption, usage, quality, reliability, cost, and business value.
• Support organizational health through goal setting, regular feedback, progress reviews, coaching, and supporting the growth of team members.
• Manage technical debt and architectural consistency to support long-term maintainability and sustainable delivery.
• Stay close to the team's technical efforts through participation in design discussions, review of technical proposals, and direct contribution to implementation when necessary.
• Identify and resolve technical challenges, delivery risks, operational issues, and cross-team blockers.
• Promote best practices regarding automated testing, CI/CD, code reviews, observability, documentation, security, and maintainable software design to improve the engineering quality of the entire team.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
• 7+ years of software engineering practical experience, including 3+ years of experience managing or leading technical teams.
• Experience leading the delivery of complex software platforms, developer tools, infrastructure systems, or enterprise-grade internal tools.
• Experience managing engineers through planning, execution, feedback, coaching, performance management, and technical decision-making.
• Experience with CI/CD, test automation, Infrastructure as Code, cloud infrastructure, containers, and production deployment workflows.
• Experience building or operating production systems that utilize LLM APIs, model providers, or Generative AI capabilities.
• Understanding of considerations for operating Generative AI systems in production, such as security, access control, observability, cost management, evaluation, reliability, and data protection.
• Experience collaborating with cross-functional stakeholders such as Product, Security, Identity, Platform Engineering, and internal customer teams.
• Strong engineering fundamentals, including system design, software architecture, operational excellence, incident response, and maintainable software design.
• Clear English communication skills, with the ability to explain technical trade-offs, risks, and priorities to both technical and non-technical stakeholders.

Preferred Qualifications

• Experience with AI gateway or LLM proxy technologies, such as Envoy AI Gateway, Kong AI Gateway, LiteLLM Proxy, OpenAI-compatible gateways, or equivalent systems.
• Experience with Model Context Protocol, MCP server or client, enterprise authorization patterns, or tool permission models.
• Experience leading teams focused on Platform Engineering, developer tools, internal tools, or enterprise self-service platforms.
• Experience with enterprise identity, access management, policy enforcement, audit logs, identity-aware proxies, API gateways, or Zero Trust architecture.
• Experience with production-grade Generative AI patterns, such as Retrieval-Augmented Generation, agentic workflows, tool use, or LLM evaluation frameworks.

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• Typically, all interviews are conducted via Google Meet.
• Job postings are currently available in both English and Japanese. Please apply to only one of them.
• While we request an English resume whenever possible, please note that if you submit a Japanese resume for any reason, we may request an English version during the selection process depending on the position.

Compensation and Benefits

• Salary commensurate with industry standards based on experience.
• Working hours: Flexible working hours.
• Annual paid leave: 20 days per year (number of days in the first year varies depending on the month of joining).
• Sick leave: 6 days per year (number of days in the first year varies depending on the month of joining).
• Holidays: Saturdays, Sundays, national holidays, and other days designated by the company.
• Social insurance: Health insurance, Welfare Pension Insurance, Industrial Accident Compensation Insurance, Employment Insurance, and Nursing Care Insurance.
• Housing allowance.
• Retirement allowance system.
• Rental car support.
• Internal training programs (software learning, language learning).

Our Commitment

• We provide equal employment opportunities and respect diversity.
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