AI-driven development practices: Apply GitHub Copilot, DevOps, MLOps, LLMOps, automated evaluation, and test automation to improve engineering productivity and solution quality for customers and internal teams. Physical AI innovation: Explore and validate use cases that connect AI with the physical world through robotics, IoT, sensors, edge AI, digital twins, and operational data across industries such as manufacturing, logistics, mobility, and smart spaces. Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field AND 8+ years of experience in technical consulting, solution architecture, technical pre-sales, or engineering leadership, OR equivalent experience. Experience translating customer challenges into technical architectures and execution plans in an AI Co-Innovation Lab, innovation center, R&D, customer co-innovation, or advanced technology validation environment. Hands-on experience designing and implementing enterprise cloud, AI, data, or application architectures. Ability to communicate clearly in Japanese with technical and business audiences. Knowledge of agent architectures, RAG, knowledge graphs, vector search, evaluation frameworks, guardrails, and security design. Practical experience with data platforms, data governance, real-time analytics, MLOps/LLMOps, DevOps, and automated evaluation or testing. Experience with Physical AI use cases involving robotics, IoT, edge computing, digital twins, simulation, manufacturing, logistics, or frontline operations. Experience representing an organization externally through customer workshops, executive briefings, technical events, community activities, or content creation. Relevant certifications or demonstrated expertise such as AZ-305, AI-102, DP-600, PL-600, GitHub, Security, Data, or AI certifications.
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