| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Web 3 Ventures | Remote |
| |||
Gemini | Remote | $152k - $213k | |||
Sei Foundation | Remote | $94k - $112k | |||
Textileio | Remote | $45k - $85k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Myshell | Remote | $98k - $110k | |||
Woo | Remote | $105k - $106k | |||
Woo | Remote | $149k | |||
Binance | Taipei, Taiwan |
| |||
Binance | Taipei, Taiwan |
| |||
Coinbase | Remote | $218k - $256k | |||
Crypto.com | Hong Kong, Hong Kong | $121k - $135k | |||
Solana Foundation | San Francisco, CA, United States | $84k - $96k | |||
DFINITY | Switzerland | $122k - $127k | |||
B2C2 | Remote | $123k - $150k | |||
TradingView | Malaga, Spain | $105k - $110k |
We're looking for a creative and technically skilled AI Agent Engineer to build next-gen AI-powered tools for our meme coin / DeFi project. If you have experience with LLMs, Telegram bots, and Web3 automation, we want you on our team.
Your mission:
- Develop AI-driven automation tools that enhance community engagement and hype.
- Build AI-powered chatbots for community support, engagement, and information delivery.
- Automate presale updates, milestone alerts, and interactive experiences.
- Integrate AI with Web3 data (wallet tracking, presale progress, referral leaderboards, etc.).
- Ensure real-time, human-like AI interactions that keep the community active 24/7.
🔧 Key Skills:
✅ Experience with LLMs (GPT, Claude, Mistral, fine-tuning models for crypto/memes)
✅ Strong background in NLP, AI chatbots, and community automation
✅ Experience building Telegram bots with real-time interaction
✅ Familiarity with Web3 tech (wallet tracking, blockchain data integration, smart contracts)
✅ Knowledge of crypto culture, meme marketing, and presale dynamics
What an AI Developer does?
An AI developer is someone who creates and builds artificial intelligence systems
Their responsibilities may include designing and implementing algorithms, creating and training machine learning models, and deploying AI systems to solve practical problems
Additionally, they may be responsible for maintaining and improving existing AI systems, as well as collaborating with other teams or individuals to integrate AI technology into larger systems.