AI Implementation Specialist

This role builds customer-specific AI based on the thinking, values, and decision criteria of business leaders, top performers, and experienced specialists. The AI is intended to operate through Slack or Teams so that organizational knowledge can be accessed more easily. The role sits between customer engagement, implementation, quality management, and product improvement.

The main work is to attend interviews led by a customer success manager and identify information needed to reproduce a person’s judgment through AI. The role provides implementation-focused input to interview design, structures the information gathered into an implementable format, and implements it using the company’s persona-definition format. Responsibilities also include designing and preparing RAG corpora, including document selection, chunking, metadata assignment, and search-accuracy validation. The AI’s output is tested and improved through repeated cycles, with customer feedback incorporated into the design and an evaluation mechanism used for accuracy improvement and version management.

As the technical counterpart to the customer success manager, the role explains AI behavior, constraints, and feasibility in language customers can understand. It presents the technical basis for what can and cannot be delivered, aligns expectations, leads reviews of quality-validation results, determines improvement priorities with customers, and translates customer requests into technical requirements and implementation approaches. The customer success manager mainly handles overall project management, relationship building, interviews as the primary interviewer, contract renewals, and upsell proposals.

The role also turns customer requests, difficulties, and usage patterns into product-improvement proposals for the product manager and development team. It identifies solutions that should be generalized into product features, documents construction processes as repeatable procedures and templates, and uses AI tools such as Claude Code, Cursor, Databricks, and Arize to automate and improve the quality of the construction workflow. Product feature development, scratch application development, infrastructure construction, new-business sales, and primary customer interviews are outside this role’s scope.

The posting describes suitable backgrounds including end-to-end requirements definition and implementation in SI or contract development, solution engineering or presales work that included implementation or proof-of-concept construction, RPA or low-code implementation support, and hands-on internal DX promotion. No specific educational requirement or years-of-experience threshold is stated. The role involves less coding than a product-development engineer but requires personally building, testing, and improving customer AI on the company’s product foundation. It is basically office-based for team coordination, with approved remote-work locations also listed in Tokyo and Yokohama. The listed offices are indoors smoke-free, with designated indoor smoking areas.