About ai&
ai& is a new global AI technology company dedicated to meeting the world's growing demand for AI. Our vision is twofold: to serve as a premier AI lab specializing in localization, and to act as a global infrastructure and compute provider. We are building a unified, optimized global platform that integrates next-generation data centers and infrastructure, heterogeneous compute serving, and advanced model services. We believe that the most effective way to build and scale AI is to own the stack from top to bottom.
At ai&, we empower small teams with the autonomy needed to tackle significant challenges. Our approach is to deconstruct large problems into manageable components and solve complex issues collaboratively. We seek highly motivated, mission-driven individuals who demonstrate strong personal agency. We value curiosity as the foundation of talent, and we are looking for people eager to develop alongside our evolving technology and expanding business.
Role Overview
As a Field Application Engineer for our AI Platform, you are the technical bridge between ai& and our customers at every stage of the commercial relationship. You will work closely with the sales team in pre-sales engagements, helping customers understand what ai& can do and how it maps to their problems. You will then stay close through onboarding, implementation, and ongoing support, making sure customers are successful on the platform.
This is a role that demands both technical credibility and communication clarity. You need to be technical enough to work with customer engineers, and articulate enough to explain complex AI and inference concepts to a general audience including business leaders, product teams, and executives. You thrive at the intersection of technology and customer problems, understanding what someone needs and figuring out how to get them there.
On the AI platform side, you will work across inference serving, model deployment, custom AI, and agentic workflows. You will represent ai&'s capabilities in the field and bring the customer perspective back into the product and engineering teams.
Responsibilities
- Technical Pre-Sales: Support the sales team in pre-sales engagements. Lead technical discovery, respond to detailed customer questions, run product demonstrations, and help customers evaluate ai&'s AI platform against their requirements.
- Technical Communication: Synthesize, explain, and articulate complex AI and inference topics clearly to a wide range of audiences — from customer engineers to business stakeholders to executives. Make the hard stuff understandable without oversimplifying.
- Customer Onboarding & Implementation: Own the technical onboarding experience for new customers. Guide them through integration, deployment, and initial configuration. Ensure they reach value quickly and on the right foundation.
- Customer Support Across the Stack: Be the technical point of contact for customers across the AI platform stack. Diagnose and resolve issues, coordinate with internal engineering teams when needed, and ensure customers always have a path forward.
- Requirements Gathering: Understand customer problems and requirements deeply. Translate them into clear technical specifications that inform product development and help the engineering team build what customers actually need.
- Proof of Concept: Lead technical proof-of-concept engagements. Design evaluations that answer the right questions for the customer and demonstrate the real-world capability of ai&'s platform.
- Customer Feedback Loop: Bring structured customer and market feedback back into ai&. Be the signal from the field that keeps the product and engineering teams informed about what matters.
You may be a fit if you have the following skills
- Technical Pre-Sales Experience: You have worked in a field application engineering, solutions engineering, or technical pre-sales role. You know how to run a technical discovery, respond to RFPs, and navigate a complex enterprise sales cycle.
- AI and Inference Familiarity: Working knowledge of AI inference, LLM deployment, model serving, and agentic frameworks. You do not need to be a researcher but you need to be able to discuss these topics credibly with a customer's ML team.
- Communication Clarity: You are exceptionally good at explaining technical topics to non-technical audiences. You can take a complex concept and make it land clearly without losing the important details.
- Customer Engineering Fluency: Technically strong enough to sit with a customer's engineering team, understand their architecture, and have a peer-level conversation about integration and deployment.
- Onboarding and Support Track Record: Experience supporting customers through technical onboarding and implementation. You are patient, thorough, and follow through until the customer is successfully running.
- Bilingual Fluency: Professional fluency in Japanese and English is required.
- Great Team Spirit: A mission-driven approach to customer work, valuing clear communication, technical depth, and collective success over individual recognition.