Work directly with business stakeholders to translate between data and business needs, analyze results, and communicate findings to senior leadership in the Tokyo-based Japan Central Ops role.
About this role
Amazon Web Services Japan hires a hands-on Senior AI Specialist Solutions Architect to help customers of all sizes adopt generative AI, machine learning and agentic technologies. Specialist solutions architects bring deep domain expertise to customers whose problems need expert-level design.
The architect becomes the trusted advisor to customers, recommending improvements in security, cost, performance, reliability and operations for their generative AI and agent projects. Internally the person relays customer needs to shape the AWS roadmap, defines cloud-native architecture patterns for a range of use cases, and shares best practices, white papers, code samples and reference architectures. The role also covers workshops, public speaking and hands-on deep dives.
Preferred qualifications include cloud certification, a track record of leading complex projects, the ability to lead a small initiative with partly defined goals, influence over customer and internal decision makers as a technical thought leader, practical experience with Retrieval-Augmented Generation, and a master's degree or PhD in a quantitative field with experience fine-tuning language models using LoRA, QLoRA, instruction tuning and RLHF.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
Similar jobs
Applied GenAI engineering role for Amazon Logistics requiring AWS data services and big-data technologies, including Redshift, S3, Glue, EMR, Kinesis, Hadoop, Hive, and Spark.
Develop machine-learning models, run experiments, and analyze large-scale data to improve product discovery, search relevance, personalization, and GenAI/LLM-powered customer experiences.
Lead software development from requirements through release and maintenance, improve architecture and development processes, and support team growth across GO's mobility products. The role may involve hands-on implementation, people management, and generative AI adoption.
Build and validate a new AI product by exploring customer problems, prototyping and improving solutions, and driving customer acquisition and adoption with engineering, design and business teams.
Leads enterprise AI implementations from requirements to production, designing architecture, data connectivity, and RAG pipelines while guiding technical standards in a hybrid Tokyo role.