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About Us
Sei is the first parallelized layer 1 blockchain. By re-writing the most widely adopted execution environment in Web3, Sei is setting a new standard in blockchain performance and scalability. Apps on Sei benefit from both the performance of web2 and the decentralization and sovereignty of web3. For more detailed information visit Sei's official website.
About the role
The Sei Development Foundation is hiring its first AI Lead - the person who transforms how the organization works by embedding AI into the daily operating fabric of every team. This is not a research role or a content role. It’s a strategy and execution role: you will audit how work gets done, identify where AI can meaningfully accelerate it, and build the workflows, prompts, and systems that make those gains permanent and scalable.
You’ll start by working closely with founders and leadership, shipping quick wins in the first two weeks and a full AI playbook within 90 days. Over time, you’ll become the organizational standard-bearer for AI adoption, the person everyone comes to when they want to work faster and think sharper. The right candidate has already built this kind of system for themselves or for a previous organization and can prove it.
Responsibilities
Workflow Audit & Opportunity Mapping
Conduct a rapid audit of current AI usage and operational workflows across the organization, identifying the highest-leverage opportunities for improvement
Build a prioritized roadmap of AI implementation opportunities ranked by time savings, output quality, and strategic impact
Identify recurring bottlenecks in research, reporting, communications, and decision-making that are strong candidates for AI-assisted automation or augmentation
Prompt Engineering & Workflow Design
Design, test, and iterate on prompts and prompt chains that deliver reliable, high-quality outputs for specific business functions (research synthesis, executive briefings, partner outreach, content drafts, etc.)
Build and document repeatable AI workflows for core operating functions including reporting, analysis, planning, and communications
Develop systematic evaluation criteria for AI output quality and reliability, so the organization knows when to trust AI outputs and when to verify
Maintain a living prompt library organized by function, with version history and performance notes