Founding Field Engineer, Japan

Zilliz is a leading AI data infrastructure company and the creator of Milvus, the world's most widely adopted open-source vector database with 45,000+ GitHub stars. Zilliz helps enterprises and AI startups make their unstructured data searchable, analyzable, and governable — turning text, images, audio, video, and more into a strategic asset for production AI.

Zilliz's technology centers on Milvus and Zilliz Cloud. Milvus is an open-source vector database purpose-built for 100-billion-scale vector search. Zilliz Cloud extends that foundation into a fully managed Vector Lakebase platform, combining the high-throughput, low-latency serving capabilities of vector databases with the openness, scalability, and economics of multimodal data lakes. Zilliz powers more than 10,000 enterprises and AI-native startups worldwide.

About the Role

What You Will Do

• Serve as the engineering-side technical counterpart for customers in Japan.
• Partner with Account Executives, Solutions Architects teams across technical discovery, POCs, onboarding, go-live readiness, production adoption, and post-sales technical engagement.
• Work directly with customer engineering, platform, data, infrastructure, and AI teams to understand their architecture, use cases, technical requirements, and operational challenges.
• Support customer POCs by helping define success criteria, validate technical requirements, troubleshoot issues, and identify the right implementation path.
• Guide customers through onboarding and production adoption, including deployment planning, architecture reviews, go-live preparation, operational readiness, and best-practice guidance.
• Help diagnose production issues, reproduce problems, analyze performance and reliability concerns, coordinate engineering escalations, and guide customers toward effective resolutions.
• Act as a bridge between customers and internal engineering teams when customer scenarios span multiple product areas or technical domains.
• Translate customer problems, product gaps, technical blockers, and market feedback into clear, actionable input for Engineering and Product teams.
• Help build Japan-specific technical knowledge, reference architectures, best practices, and documentation.

Who You Are

What We Are Looking For

• Strong hands-on technical background in database systems, distributed systems, data infrastructure, cloud infrastructure, Kubernetes, storage systems, search infrastructure, platform engineering, or site reliability engineering.
• Experience working with production systems, with a strong understanding of reliability, scalability, performance, troubleshooting, and operational best practices.
• Ability to understand complex customer architectures and translate ambiguous technical problems into clear next steps.
• Experience or strong interest in supporting customer POCs, onboarding, go-live readiness, production adoption, and post-sales technical engagement.
• Strong communication skills, with the ability to explain technical concepts clearly to both customer engineering teams and internal engineering stakeholders.
• Strong business sense and the ability to connect technical problems with customer value, adoption, and product impact.
• Comfort working across multiple engineering domains and coordinating with internal teams to resolve customer-facing technical issues.
• Native or fluent Japanese communication skills.
• Business-level English, with the ability to collaborate effectively with global engineering and product teams.

Nice to Have

• Experience with database internals, query engines, storage engines, indexing, vector search, search infrastructure, or modern data infrastructure products.
• Experience at a data infrastructure, database, AI infrastructure, cloud infrastructure, or developer tools company.
• Experience supporting enterprise customers through POCs, technical evaluation, onboarding, deployment, troubleshooting, production adoption, or escalation management.
• Familiarity with AI infrastructure, machine learning systems, RAG, embeddings, vector databases, or modern data platforms.
• Prior exposure to pre-sales, post-sales, customer success engineering, field engineering, or technical account management.

Why This Role Matters