Job Description
Key Responsibilities
-
Design and implement Electron-based desktop applications for prompt workflow visualization, process inspection, and self-service dashboards for non-engineering stakeholders.
-
Contribute to JavaScript/TypeScript components that enable LLM orchestration, AI workflow interoperability, pipeline automation, and MCP-compatible connectors.
-
Build and extend evaluation frameworks for verifying agent outputs and system reliability, including LLM-as-judge metrics, structured validation, and automated feedback loops.
-
Instrument operational observability tooling (e.g., LangFuse, OpenTelemetry, custom metrics) and develop automated dashboards to surface runtime insights and model performance trends.
-
Participate in the full engineering lifecycle including design reviews, implementation, testing, CI/CD integration, and Git-based collaboration workflows.
-
Collaborate closely with platform engineers and researchers on benchmark selection, failure analysis, prompt optimization, and quantitative evaluation methodologies.
Basic Qualifications:
-
Currently enrolled in a Bachelor’s, Master’s, or Ph.D. program in Computer Science, Software Engineering, Electrical Engineering, or a related technical field.
-
Strong proficiency in JavaScript/TypeScript and modern frontend/backend development practices.
-
Experience with Electron Framework, including desktop application development, IPC communication, and renderer/main process architecture.
-
Familiarity with AI agent systems, LLM tooling frameworks, orchestration pipelines, or evaluation workflows.
-
Understanding of CI/CD fundamentals, automated testing pipelines, artifact publishing, and developer productivity tooling.
-
Experience designing evaluation or verification systems for AI outputs, structured data validation, or workflow automation.
-
Strong communication and documentation skills with the ability to clearly present technical ideas, PRs, reports, and experimental findings.
Preferred Qualifications:
-
Experience building internal AI developer tools, observability platforms, or workflow orchestration systems.
-
Familiarity with modern AI infrastructure frameworks such as LangFuse, OpenTelemetry, MCP, or related tooling ecosystems.
-
Experience with prompt engineering, automated evaluation pipelines, or agent reliability optimization.
-
Knowledge of modern frontend application architecture and performance optimization for Electron-based systems.
-
Experience working in fast-paced engineering environments with rapid iteration cycles and cross-functional collaboration.
-
Contributions to open-source projects or prior experience developing scalable AI infrastructure platforms.
-
Self-motivated and proactive in solving problems.
-
Comfortable operating in fast-moving, ambiguous environments.
-
Strong in debugging, systems thinking, and iterative problem solving.
-
Able to quickly learn unfamiliar systems and contribute meaningful improvements.
-
Clear communicators who collaborate effectively and provide thoughtful feedback.
-
Passionate about building reliable AI-native tools and infrastructure.
-
A fun, supportive and engaging environment.
-
Infrastructures and computational resources to support your work.
-
Opportunity to work on cutting edge technologies with the top talents in the field.
-
Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
-
Competitive compensation package.
-
Snacks, lunches, dinners, and fun activities.