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We are building next-generation Web3 infrastructure and are looking for a motivated engineering early career talent to grow alongside us. You will work directly with our core team on real-world challenges — from optimizing real-time big data pipelines to integrating AI-assisted tooling into our development workflow. This is a hands-on role with meaningful ownership from day one.
Learn and work with real-time big data components such as Kafka, Flink, or Spark Streaming; identify bottlenecks and contribute to performance optimizations.
Participate in Web3 project development — including on-chain data ingestion, smart contract interaction, and blockchain analytics features.
Apply AI tools and LLM-assisted workflows (e.g., code generation, automated testing, documentation) to accelerate development velocity.
Collaborate in English with cross-functional teammates on engineering discussions, code reviews, and technical documentation.
Proactively explore unfamiliar technologies, ask good questions, and share learnings with the team.
Currently pursuing or recently completed a degree in Computer Science, Software Engineering, or a related technical field.
Strong genuine interest in software development — you build things in your spare time, follow technical communities, or experiment with side projects.
Fluent spoken and written English — comfortable participating in technical meetings, writing documentation, and communicating blockers clearly.
Self-driven and proactive — you do not wait to be told what to learn; you identify gaps, seek resources, and take initiative without prompting.
Available to commit a minimum of 4 days per week throughout the internship period.
Familiarity with blockchain concepts — transactions, wallets, smart contracts, or DeFi protocols.
Exposure to distributed systems, stream processing, or database design.
Prior experience using AI coding assistants (Copilot, Cursor, Claude Code, etc.) in a real project context.
Hands-on experience with production Web3 systems, mentorship from a senior engineering team, direct exposure to real-time data architecture, and a front-row seat to how AI is reshaping how software gets built.
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