AI Engineer - LLM Adoption Department (LLMAD)

The LLMAD team drives adoption of Rakuten AI and open-source LLMs hosted within our own environment.

We're hiring AI Engineers who can be embedded directly inside business units to drive real adoption of in-house large language models in place of third-party alternatives.

As an AI Engineer you will be embedded inside a business unit's engineering team and build with them day to day: implementing agent workflows and integrations, iterating on prompts, running evaluations, and getting features live in production on our in-house models.

You will work on an engagement alongside a senior engineer who sets the overall agent architecture and model direction, and you will take growing ownership of the delivery as you build depth.

This is hands-on applied LLM work, close to the product.

Embed inside a business unit's engineering team and implement agent and tool-use workflows for their use case - function calling, multi-step flows, retrieval, guardrails, and fallback handling - writing production code in their codebase.

Get features from prototype into production and support them there: debugging failures, tightening latency and cost, and fixing what breaks.

Run task-level evaluations of in-house and open-source models for your use case, and extend and maintain the eval sets and harnesses together with the business unit.

Design and iterate prompts, output schemas, and tool definitions - versioned and measured against evals rather than tuned by feel - and help narrow quality problems down to the prompt, the retrieval, the model, or the data.

Support migrations from third-party APIs to our in-house models, and surface the gaps you find to the senior engineer on the engagement and to our model and platform teams.

Document what worked as reusable recipes, examples, and starter templates for the team's shared library, and help business unit engineers adopt our tools and APIs.