Software Engineer (Professional Research Personnel)
Summary
Researches and builds AI agent systems using MCP/A2A, React/Next.js, Node.js, and cloud tools; validates tech via proofs of concept and deploys production-grade services with monitoring.
You will research and validate AI agent technologies, assess product applicability through proofs of concept, and develop AI-centered full-stack products. You will design AI agent features, build Agentic AI services, use AI coding tools, and operate reliable production systems with monitoring, logging, and error handling.
Responsibilities
- Research and validate AI agent technologies, including MCP/A2A architectures and multi-agent orchestration
- Assess product applicability through proofs of concept
- Develop AI-centered full-stack products across React and Next.js frontends, Node.js backend APIs, and data models
- Design new features for MCP/A2A-based AI agent products
- Build Agentic AI services that solve business problems
- Use AI coding agents such as Claude Code and Codex to improve development productivity and code quality
- Establish monitoring, logging, and error-handling systems
- Take responsibility for stable production operations
Requirements
- Master's degree or higher, including completion of an integrated master's and doctoral program
- Ability to complete the three-year mandatory service period for professional research personnel by age 35
- Experience independently completing a project from planning or problem definition through a working result
- Ability to develop both TypeScript-based frontend applications with React and Next.js and backend applications with Node.js
- Ability to actively use AI coding tools such as Claude Code and Codex while critically validating and improving AI-generated results to production quality
- Understanding of RDBMS and NoSQL database design
- Understanding of Git version control and CI/CD pipelines
- Experience building and operating Agentic AI or multi-agent systems
- Experience developing AI or LLM services, prompt engineering, and agent design
- Research experience in AI/ML, distributed systems, or systems software
- Experience publicly sharing results through papers, open-source contributions, or technical blogs
- Experience operating cloud infrastructure such as GCP and deploying containerized applications with Docker and Kubernetes
- Experience developing chatbots or conversational interfaces and considering conversational flows and response speed