【JAPAN AI】Research Engineer, LLM/Agent / English

About JAPAN AI

JAPAN AI, Inc. was established in April 2023 as a group company of Geniee, Inc. (TSE Growth Market) with the mission of dramatically expanding human potential through AI technology. We drive cutting-edge AI R&D both domestically and internationally.

Our ambition goes far beyond building AI chatbots. We are building "the brain of the enterprise" — a next-generation core system where AI autonomously executes business operations by integrating all of a company's SaaS tools. With JAPAN AI STUDIO at the center, we are implementing a world where — given a database — no separate application is needed; AI performs the work and returns only the results.

Through the transformative power of AI, we aim to create new value and contribute to the advancement of society as a whole. Join us in leading AI innovation and shaping a future where technology empowers people to achieve more.

Related URLs

• Our Website
• Company Introduction Materials
• Tech Blog
• Careers

Why We're Hiring

JAPAN AI STUDIO aims to function as "the brain of the enterprise" — integrating every SaaS tool a company uses and enabling AI agents to autonomously execute hundreds of workflows. However, realizing this vision requires breaking through "frontier challenges" that current agent technology cannot solve:

• Reasoning quality limits when searching and integrating information across multiple SaaS platforms
• Long-term memory design that retains context across extended business processes
• Multimodal handling that unifies text, images, audio, and structured data
• Low-latency inference in environments where hundreds of companies operate simultaneously

Over the past year, adoption of LLM-powered agent systems has accelerated rapidly — from coding and research to customer support and security. Looking ahead to a future where AI agents handle increasingly complex tasks end-to-end or in collaboration with humans, JAPAN AI is strengthening the team that will:

Build more effective agents for long-horizon tasks
Design coordination mechanisms for agents to collaborate at various scales
and accomplish larger objectives
Solve the necessary challenges — novel harness design, infrastructure improvements, fine-tuning — to maximize agent performance

Mission

"Solve the problems that make today's agents give up."

Take on frontier challenges that today's AI agents cannot solve. Break through the quality limits of reasoning, retrieval/planning, long-term memory, and tool use. Pave the way — through research — for a future where hundreds of workflows running on JAPAN AI STUDIO operate smarter, faster, and more safely.

Role & Expectations

As a Research Engineer, you will lead cutting-edge and applied research in AI/LLM/ML:

• Conceive, develop, and compare different agent harnesses (memory, context compression, inter-agent communication architectures, etc.)
• Design and implement rigorous quantitative benchmarks for large-scale agentic tasks
• Support automated evaluation of models and prompts, ensuring quality across the entire lifecycle — from training to production
• Collaborate with the product organization to solve the hardest challenges in applying agents to products
• Create and optimize training data mixes to improve agent task performance and usability
• Transfer research outcomes to the Agentic Product Engineer team, raising quality across all products

Writing papers is not the goal. We prioritize applying research to production and delivering results to users in a live environment serving approximately 200 companies.

Why You'll Love This Role

• Research that powers "the brain of the enterprise" — This is not about improving chatbots. You will build the technical foundation for a next-generation core system where AI autonomously executes operations by integrating all enterprise SaaS — and you will do it through research.
• Research → Production, directly connected — Your methods are immediately deployed to a production environment used by ~200 companies. This is not research that ends with a paper — you will feel real-world impact.
• Cutting-edge AI research in practice — Work on the industry's frontier challenges: breaking reasoning quality limits, designing long-term memory, orchestrating multi-agent coordination, and more.
• Research and publication, side by side — We encourage paper publication and tech blog writing, and actively support collaboration with academic institutions and OSS communities.
• Impact through technology transfer — Transfer your methods to the Agentic Product Engineer team and exercise leadership in raising quality across all products.
• Rapid-growth environment — In a startup that has grown to 200+ people and 9 products in just 3 years, you will have significant autonomy in technical decision-making.

Job Description

• Agent Research & Development
  • Conceive, develop, and compare different agent harnesses (memory, context compression, inter-agent communication architectures, etc.)
  • Research and develop new reasoning, planning, and retrieval methods
  • Develop technologies for multimodal and long-context handling
  • Survey, reproduce, and improve upon the latest research papers
• Evaluation & Benchmarking
  • Design and implement rigorous quantitative benchmarks for large-scale agentic tasks
  • Design synthetic data generation and evaluation benchmarks
  • Support automated evaluation of models and prompts (across the full lifecycle from training to production)
• Production Problem-Solving
  • Optimize inference latency and cost (quantization, distillation, caching, etc.)
  • Create and optimize training data mixes
  • Advance agent evaluation frameworks
  • Improve quality and tune performance in production environments
• Knowledge Transfer & Outreach
  • Transfer technology and mentor the Agentic Product Engineer team
  • Collaborate with academic institutions and OSS communities

Key Results (KR/Metrics)

• Benchmark score improvement rate (internal and public benchmarks)
• Number of novel methods shipped to production (per quarter)
• Inference latency and cost reduction rate
• Number of papers and technical blog posts published
• Number of internal knowledge transfers completed

Team Structure

Approximately 120 members are part of the development organization.

• Research Engineers work across the following groups:
  • JAI Lab — AI research and development
  • AI & Model — Model training and optimization
  • Voice & Tel — Speech AI and telephony systems
• Closely collaborating roles:
  • Agentic Product Engineer — Agent feature development (primary research transfer target)
  • Agent Harness Engineer — Agent execution infrastructure
  • AI Quality Scientist — Evaluation pipeline collaboration
  • Product Manager — Product design and prioritization

You May Be a Good Fit If You

• Master's or Ph.D. in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Mathematics, Physics, or related fields
• Experience developing complex agentic systems using LLMs
• Significant hands-on experience in software engineering and ML
• Experience with LLM prompt engineering and/or building products with language models
• Experience with large-scale model training and inference using PyTorch or JAX
• Deep understanding of LLM and Transformer architectures
• Ability to read, reproduce, and improve upon research papers
• Strong implementation skills in Python (production-quality code)
• Language requirement (at least one of the following):
  • Japanese: Fluent — able to discuss product development without friction
  • English: Business level

Strong Candidates May Also Have

• Experience with large-scale reinforcement learning on language models
• Experience designing and implementing multi-agent systems
• Publications at top-tier conferences (NeurIPS, ICML, ACL, EMNLP, or equivalent)
• Hands-on experience implementing alignment techniques such as RLHF or DPO
• Experience with multimodal models (e.g., Vision-Language models)
• Background in agent evaluation or AI safety research
• Ph.D. in CS, ML, NLP, or a related field
• Ability to communicate research findings in English

Tech Stack

• Languages: Python (research / framework), TypeScript / React / Next.js (frontend) / NX
• ML/AI: PyTorch, JAX, Transformers, vLLM, Weights & Biases
• Infrastructure: GCP (containers / K8s), Docker
• Tools: Slack, Confluence, Linear, Google Workspace, GitHub, Notion
• AI Dev Support: Claude Code MAX Plan, Cursor, ChatGPT, Devin
• Hardware: Mac (Apple Silicon), dual monitors

Learning & Development Support

• AI Tool Usage Support
  • Company covers the cost of using AI tools such as JAPAN AI SaaS services, Cursor, ChatGPT, Claude, etc.
• Development Tool Support
  • If a desired development tool is paid, the cost is covered (up to ¥30,000 per year)
• Book Purchase Assistance
  • Company covers the cost of purchasing books for learning, such as technical books (up to ¥30,000 per half-year)
• Language Learning / Qualification Support
  • Company covers the cost of Japanese or English learning programs and qualification acquisition
• Refresh Allowance
  • Company covers the cost of services used for personal refreshment (up to ¥5,000 per month)
  • e.g., gym, yoga, chiropractic, aquarium, movies, theme park tickets, etc.
• Housing Allowance
  • Housing allowance provided for those living in designated areas (up to ¥30,000 per month)