Design and deploy intelligent agents that translate mission intent into safe, adaptive plans for multi-domain unmanned systems, integrating LLM reasoning with autonomy software and edge hardware.
AI Platform Engineer (MLOps/LLMOps)
📜 Description
- Design, implement, and operate shared MLOps/LLMOps platforms and workflows.
- Create traceable systems for models, prompts, agent configurations, evaluation data, experiments, and releases.
- Partner with AI quality evaluation engineers and product teams on evaluation, regression testing, and release decisions.
- Monitor LLM output quality, safety, consistency, latency, cost, and usage; establish alerts and rollback mechanisms.
- Automate AI workload development and operations with CI/CD, Infrastructure as Code, containers, cloud platforms, and observability tools.
- Build safe, auditable agent workflows for code generation, modification, and review, including validation policies.
🛠️ Requirements
- 2+ years of professional experience in MLOps, LLMOps, or Platform Engineering
- Experience designing, implementing, and operating platforms that support the development, evaluation, deployment, and operation of LLM systems
- Experience automating development or operational processes using CI/CD, Infrastructure as Code, container technologies, and cloud services
- Software development experience using Python
- Business-level proficiency in both English and conversational-level Japanese
- Experience building feedback loops for AI quality improvement using user feedback, usage logs, evaluation results, support inquiries, incident information, and related data
- Experience designing and operating systems that consider cost, latency, rate limits, availability, and security when using LLM APIs
- Experience building mechanisms for AI safety, security, governance, and auditability
- Experience designing, introducing, and operating development-support systems that use AI agents for code generation, code review, testing, or related engineering workflows
- A proactive mindset and demonstrated ability to identify challenges in emerging technical areas and drive them from prototyping through the implementation of operationally sustainable solutions
✨ Benefits
- ・Competitive Salary - Based on experience
- ・Work Hours - Flexible working time
- ・Paid Holiday - 20 days per year (prorated)
- ・Sick Leave - 6 days per year (prorated)
- ・Japanese Social Insurance - Health Insurance
- Pension
- Unemployment Insurance
- Long-term care insurance
- ・Housing Allowance
- ・Retirement Benefits
Full job description
TEAM
Toyota is redefining what it means to move. We're challenging the current state of mobility by enhancing the movement of people, goods, information and energy. Centered around three core concepts - A Living Laboratory™, Human-Centered, and Ever Evolving City™ - Woven City serves as a test course for mobility to fulfill our purpose of well-being for all.
We do this by bringing together a diverse community of people with a shared passion for the future of mobility to co-create, develop and refine innovative products and services. This cross-section of social infrastructure, mobility, and people provides a unique opportunity for inventors, residents and visitors to interact seamlessly with new technologies throughout daily life in an environment that emulates a real city.
For more information about Woven City, please visit: https://www.woven-city.global/
WHO ARE WE LOOKING FOR?
This position is not responsible for developing individual product features. Instead, the mission is to design, implement, and operate the shared platforms, workflows, and guardrails required for AI product development, evaluation, release, and operations. By reducing manual work and reliance on individual knowledge, you will improve development productivity, operational efficiency, and the quality and reliability of AI outputs across the organization.
From an MLOps perspective, you will build and improve systems that support reliable operations through the management of models, data, experiments, evaluation results, and releases; CI/CD; infrastructure configuration management; monitoring, log collection, and alerting; and automation of incident response. You will also build mechanisms with validation workflows, policies, and evaluation methodologies, including agent-based code review.
From an LLMOps perspective, you will drive the design and operation of feedback loops that collect and organize user feedback, usage logs, AI quality evaluation results, incidents, and failure cases, and use these insights to improve agents and tools. You will be expected not only to experiment with emerging technologies, but also to turn them into solutions that can be continuously used in real development environments, with due consideration for security, quality, reproducibility, and operational sustainability.
You will work closely with product development teams, ML engineers, and security and cloud infrastructure stakeholders to evolve a reusable AI Platform that supports multiple products.
This position reports to a functional leader. The work arrangement is hybrid, and travel to Woven City several times per month is required.
RESPONSIBILITIES
MINIMUM QUALIFICATIONS
NICE TO HAVES
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