We're looking for a full-stack engineer who operates at the intersection of AI Agents and blockchain. You'll build scalable, high-performance AI-driven applications, deeply integrate cutting-edge LLM models, and bring strong engineering depth across both Web2 and Web3 stacks — all in service of building next-generation decentralized intelligent applications.
This is not a pure frontend or backend role. We're looking for a true full-stack architect and builder.
Responsibilities
Core Application Development: Design and implement full-stack applications and SDKs centered on blockchain middleware and infrastructure — deeply embedding AI Agent capabilities (LLM workflow orchestration, RAG, Multi-Agent collaboration) into on-chain data processing, cross-chain protocol integration, and smart contract interaction; and build the integration layer between AI agents and blockchain tooling (MCP, Tool Calling, native SDKs, etc.).
Backend Engineering: Build highly available, scalable backend services using Python, Node.js, or equivalent modern frameworks.
Frontend Development: Deliver high-quality, user-friendly interfaces using modern frontend frameworks (e.g., React).
Web3 Integration: Independently develop smart contracts and integrate seamlessly with major blockchain networks (e.g., EVM-compatible chains).
Architecture & Standards: Draw on hands-on experience to define engineering standards, establish reusable architecture patterns, and drive the team's technical growth.
Vibe Coding Practice: Apply Specification Engineering as a methodology to drive AI-assisted delivery (Cursor, Claude Code) with discipline; codify best practices into team-wide standards (CLAUDE.md, .cursor/rules, prompt template libraries) under version control to continuously raise the team's collaborative efficiency.
Technical Insight & Innovation: Stay ahead of the AI + blockchain frontier, produce actionable technical insights, and drive continuous improvement of products and solutions.
Requirements (At least 3 required)
Frontend & Backend Proficiency: Fluent in at least one frontend framework (e.g., React) and one backend language (Python or Node.js); experienced in RESTful / GraphQL API design and performance tuning; disciplined about writing unit, integration, or E2E tests as a quality guarantee.
AI Engineering Depth: Deep understanding of LLM capabilities, prompt engineering, and inference cost/latency trade-offs; proven experience taking AI features from prototype to production, including observability, fault tolerance, and evaluation pipelines.
Web3 Engineering: Hands-on experience deploying and debugging smart contracts on mainnet or testnet; solid grasp of on-chain data structures and common security vulnerabilities — not just contract syntax.
Full-Stack Delivery: Track record of independently shipping complete AI-driven applications or SDKs — owning tech selection, architecture, and implementation end-to-end without relying on others to catch the gaps.
Engineering Culture: Experience leading or contributing to team engineering standards (e.g., code review processes, technical documentation, AI-assisted development guidelines); able to turn personal expertise into team-wide assets.
Nice to Have
The following will position you for a more senior scope and impact:
AI Protocols & Ecosystem: Hands-on experience building MCP Servers or integrating multi-agent collaboration protocols (e.g., A2A); familiar with the evolving landscape of AI tooling standards.
Blockchain Infrastructure & Middleware: Deep understanding of mainstream blockchain infrastructure and protocol layers — including L2 Rollup architecture (OP Stack / zkEVM), cross-chain interoperability (LayerZero, CCIP, IBC), on-chain payment protocols (x402, streaming payments), and privacy protocols (ZK proof systems, Aztec, private DeFi) — with engineering experience in one or more of these areas.
AI Product Thinking: Ability to independently identify AI opportunities in business contexts and drive product design and iteration from a technical perspective.
Open Source / Community Presence: Active open source contributions or visible technical influence in the AI or blockchain space (writing, talks, GitHub, etc.).
0-to-1 Experience: Background in startups or greenfield product builds; able to validate ideas quickly and ship under resource constraints.
