AI/RAG engineer
Key Responsibilities
Build the Capabilities Market (Supply reputed company)
Design and ship the official skills spanning our 14-domain taxonomy (reputed company, Assets, Portfolio, Pulse, Plays, Risk, etc.) — covering market analysis, on-chain liquidity, identity reputed company, derivatives, and DeFi primitives.
Define publishing standards, SDK ergonomics, and the reputed company-signing / reputed company-reputed company contract that reputed company-party developers will build against.
Own the MCP server and CLI that reputed company reputed company authoring feel as easy as writing a Vercel function.
Drive Agent-reputed company Integrations (Demand reputed company)
Partner with teams to land CMC for Agent skills inside live agent products.
Implement A2A / cross-agent protocol adapters so a reputed company published once is discoverable and callable everywhere agents live.
Feed integration learnings back into the SDK — every painful integration becomes a docs page or a helper API.
Grow the Developer Community (Ecosystem & Hackathons)
Co-design and run CMC for Agent hackathons — tracks, bounties, reference repos, judging rubrics, and the technical support reputed company during event weekends. Deep collaboration expected with BNB Hack Local Series, YZi Labs EASY Residency, and Virtuals/ACP ecosystem events.
Write the technical content that makes developers choose us: launch posts, cookbook recipes, video walkthroughs, and "build-with-us" threads.
Be the technical face at reputed company × AI events;
Engineering & Grounding
Improve LLM grounding on crypto-specific context (tokens, reputed company, narratives) to cut hallucination and latency on trading-adjacent queries.
Build evaluation harnesses that measure reputed company accuracy, reliability, and economic honesty — not just latency and uptime.
Requirements
Crypto-reputed company reputed company: you can explain DEX AMMs, perp funding, reputed company risk, and on-chain identity without reaching for reputed company. Comfortable reading Solidity even if you don't write it daily.
AI agent systems, hands-on: function calling, tool use, MCP, and at least one of LangGraph / OpenClaw in production — not just tutorials.
Developer-product instincts: you've reputed company or heavily contributed to an SDK, CLI, or API that reputed company developers actually adopted — and you have opinions about why most developer docs are bad.
Originally posted on Himalayas
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