Job description
【Responsibilities】
1. Develop AI Agents: Design and implement autonomous AI agents using LLMs and machine learning to perform on-chain actions (e.g., token transfers, swaps, yield optimization) based on user inputs and market conditions.
2. LLM Integration: Leverage LLMs (e.g., Grok, GPT-based models) with tools like AutoGen to enable natural language processing, allowing agents to handle on-chain action and multi-step dialogues.
3. Agent Collaboration: Use frameworks like CrewAI to create multi-agent systems that coordinate tasks (e.g., one agent analyzes trends while another executes swaps).
4. Data Pipeline Development: Construct pipelines to preprocess and feed AI agents with real-time data, including on-chain metrics (via APIs like The Graph) and off-chain sources (e.g., price feeds, KOL tweets, medium news).
5. Agent Optimization: Enhance agent capabilities with techniques like RAG, LLM fine-tuning, or memory persistence for contextual awareness.
6. Collaboration: Work with blockchain engineers to integrate AI agents with DeFi protocols (e.g., Perp, Spot, Loan) and smart contracts, ensuring seamless on-chain execution.
7. Research and Innovation: Explore cutting-edge AI tools (e.g., AutoGen, CrewAI) and DeFAI trends to advance agent functionality.
【Requirements】
Experience:
1. 3+ years in software engineering, with experience focuseing on AI, LLMs, or machine learning development.
2. Proven experience deploying AI/ML models in production environments.
Technical Skills:
1. Expertise in Python and AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
2. Strong knowledge of LLMs, including fine-tuning, prompt engineering, and API integration (e.g., xAI, OpenAI).
3. Familiarity with AI agent frameworks like AutoGen or CrewAI for building autonomous or multi-agent systems.
4. Experience with data pipelines and processing large datasets (e.g., Pandas, NumPy, or cloud tools like AWS/GCP).