Key Responsibilities
Work closely with frontline R&D teams to identify repetitive tasks, collaboration bottlenecks, and waiting time waste through interviews and data analysis, and break them down into actionable engineering problems.
Rapidly develop and deploy AI agents and automated workflows, integrate them with code repositories, R&D platforms, knowledge bases, and collaboration tools, and continuously iterate them to production-ready standards.
Drive small-scale pilots, collect feedback, assist teams in adopting new tools through training and documentation, and consolidate successful solutions into reusable capabilities.
Establish performance metrics (delivery cycles, defect rates, adoption rates, etc.) and design evaluation, monitoring, and security mechanisms (permissions, auditing, data protection).
Qualifications
At least 3 years of experience in software engineering, solutions, or developer tools, with the ability to independently complete the entire process from requirements to operations.
Proficiency in at least one mainstream programming language, such as Python, TypeScript, Go, or Java.
Practical development experience with LLMs or AI agents; familiarity with prompt design, RAG, tool invocation, workflow orchestration, and evaluation.
Ability to integrate AI into CI/CD pipelines, code repositories, project management tools, and internal data systems; familiarity with APIs, databases, permissions, monitoring, and cloud-native deployments.
Skilled at communicating with product, R&D, testing, and management teams; results-oriented; able to rapidly validate and iterate in ambiguous environments.
Bonus Qualifications
Experience with blockchain, wallets, exchanges, DeFi, on-chain data, or cryptocurrency products.
Familiarity with R&D efficiency and DevEx tooling; experience implementing automated testing, CI/CD, or incident response.
Understanding of AI security, observability, and data protection.
- Translated with DeepL.com (free version)