AI Agent Engineer

What You'll Do

• Design and build an AI coding agent system that enables end-to-end automation from human instructions to pull request (PR) submission.
• Build isolated devbox sandbox environments to ensure agents operate securely and independently.
• Develop and maintain the agent Skills ecosystem and CLI tool chain, exposing internal platforms and tools (including data pipelines, task tracking, code search, and CI/CD systems) through unified interfaces for AI agents.
• Design the agent blueprint system by encoding common engineering tasks such as bug fixing, feature implementation, code migration, and test generation into reusable workflows.
• Establish an agent effectiveness measurement framework and dashboards covering key metrics such as task success rate, CI pass rate, code review approval rate, and average completion time.
• Collaborate with engineers across the company to gather feedback, continuously improve agent capabilities, and promote AI-native software development practices.
• Evaluate and experiment with cutting-edge AI development tools, including Claude Code, Goose, Codex, and related technologies, to identify and adopt the optimal technology stack.
• Contribute to the open-source ecosystem by open-sourcing the agent core and reusable capability modules, actively engaging with global communities, leveraging external feedback to drive iteration, and helping define and promote AI-native engineering standards.

What We're Looking For

• 3+ years of software engineering experience with strong system design and back-end development skills. Deep expertise in at least one of Python, TypeScript, or Go.
• Strong understanding of AI and LLM application development, with hands-on experience building and using agents at scale. Familiarity with prompt engineering, agent frameworks, and memory systems.
• Solid knowledge of the modern developer tooling ecosystem, including CI/CD, code search, sandboxing and containerization, build and release systems, and Infrastructure as Code (IaC).
• Familiarity with quantitative trading infrastructure is a plus, including market data systems, trading protocols, and low-latency architectures; however, learning ability and engineering excellence are valued more highly than prior domain experience.
• Excellent communication and collaboration skills, with the ability to work effectively across teams and drive organization-wide workflow transformation.
• Self-driven and highly curious about emerging AI technologies, with the ability to independently explore, prototype, and validate new ideas.
• Strong belief in, and enthusiasm for shaping, the future of software development in the AI era.

We believe AI-native software engineering will fundamentally reshape how products are built, and we're looking for builders who want to help define that future.