Responsibility

• Contribute to backend and/or full-stack feature development, testing, and release for core products/platforms, delivering production-ready code.
• Collaborate with senior engineers on module design, API/interface definition, system integration, and deployment (including logging, monitoring, and performance optimization).
• Write and maintain automated tests and CI/CD-related configurations to improve development efficiency and code quality.
• Support the engineering deployment of AI/LLM capabilities based on business needs, such as integrating LLM APIs, building basic RAG pipelines, and embedding tool/agent capabilities into existing systems.
• Help build and maintain datasets and benchmarks for evaluation/regression, track online performance, and assist with debugging and fixing issues.
• Produce necessary technical documentation and communicate effectively across teams.

Requirements

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
• Solid software engineering fundamentals: data structures and algorithms, object-oriented design, common design patterns, and coding best practices.
• Proficient in at least one primary programming language for engineering work; Python is required. Experience with Java/Go/TypeScript/JavaScript is a plus.
• Familiar with common engineering tools and workflows: Git, basic Linux, debugging skills; understanding of unit/integration testing, RESTful APIs, and databases (SQL/NoSQL).
• Some AI/LLM project or internship experience is sufficient (no deep research required), e.g., prompt engineering/function calling, RAG, vector databases, or experience integrating frameworks like LangChain/LangGraph is a plus.
• Strong ownership, good communication and collaboration skills, and the ability to learn quickly and deliver.
• Able to commit to at least 6 months, 5 days per week.

Nice to Have

• Experience shipping web/backend services; knowledge of caching, message queues, concurrency, and performance tuning.
• Familiarity with containerization and deployment (Docker/Kubernetes), cloud platforms (AWS/GCP/Azure), or observability (Prometheus/Grafana/ELK).
• Exposure to LLM evaluation, prompt iteration, data feedback loops, or basic fine-tuning workflows.

• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.