Technical Solutions Engineer (Japanese)

Deploy Sakana AI's products inside enterprise customers, drive them from PoC to company-wide adoption, and feed learnings back into improving products. Requires business-level Japanese and conversational English.

Provides technical support to Datadog's premier customers in Japanese, handling complex issues and ensuring timely resolution. Requires fluency in Japanese and strong troubleshooting skills.

This Solutions Engineer role bridges the gap between technical and business teams, providing technical expertise during sales and implementation. The position involves designing solutions, integrating APIs/SDKs, and ensuring client technical requirements are met. Key responsibilities include pre-sales support, technical troubleshooting, and collaborating with product and engineering teams.

This role provides customer support in Japanese for Amadeus travel solutions, handling inquiries and resolving issues. It requires bilingual proficiency in Japanese and English, along with strong customer service skills to assist clients effectively.

This role focuses on owning agent features end to end, from problem definition and design to shipping and measuring quality in production. The scientist will contribute to the design, development, and productionization of enterprise AI agents including Marketing, Strategy, Data Analysis, and Sales and Service agents, building agent capabilities as reusable skills and MCP tools. Requires 2+ years of experience in ML or software engineering, hands-on experience building at least one LLM or agent application end to end, and strong SQL and data reasoning skills.

This role serves as a strategic bridge between Appier's product applications, client data, and business requirements, architecting and implementing solutions using existing products. Requires SQL and Python for data extraction and modeling, dashboard development with Tableau or Looker, and experience with A/B testing and data governance. The consultant translates client feedback into product requirements and collaborates with Product, Customer Success, and Sales teams.

This role focuses on developing and deploying machine learning models and evaluation frameworks for enterprise AI solutions, with a strong emphasis on LLM output quality and A/B testing. The scientist will work end-to-end from problem definition to production, collaborating with PMs and engineers, and will also monitor post-launch performance and communicate risks. Requires a Master's or PhD in a relevant field, at least 2 years of ML experience, and hands-on experience with classification, regression, ranking, retrieval, and LLM-as-a-judge evaluation.