AI Product Engineer

Lightning Labs builds the infrastructure that makes Bitcoin work as a global payment network. Our protocols: the Lightning Network, Taproot Assets, and L402, are used by developers all around the world and are increasingly the rails that AI agents use to pay for services, stream value, and transact autonomously. We are looking for an AI Product Engineer to help us move faster everywhere at once.

• Build demos and developer experiences that show what's possible on Lightning. End-to-end working applications that showcase Lightning payments, L402-gated APIs, Taproot Assets, and agentic workflows. These demos are how we communicate the value of our platform to developers and partners.
• Automate and augment internal workflows by partnering with engineering, product, business development, and marketing teams to identify where AI can eliminate manual work. Build the tools, scripts, MCP servers, and integrations that make the whole company faster.
• Ship features across products including Terminal Web, LND, and new products. You'll write production code, not just prototypes, but you'll also know when a prototype is the right answer.
• Work autonomously with minimal direction. Understand the company's priorities, identify where you can have the most impact, and execute. Context switch across projects and teams while maintaining quality.

• You build and ship production-quality software. You have a portfolio, GitHub profile, or set of projects that demonstrate this, we'd love to see them.
• You use AI-native development tools (Claude Code, Cursor, Codex, or similar) as part of your daily workflow, not as a novelty.
• You're comfortable across the full stack. Our work spans TypeScript, React, Go, Python, and whatever else the problem requires. Go experience is a plus.
• You have strong product instincts and can translate between technical and non-technical contexts. You'll work directly with business development, marketing, and product, not just engineering.
• You're familiar with agentic AI patterns: tool use, MCP, multi-step workflows, and integrating LLMs into real systems.
• You're self-directed with a bias toward action. You thrive in ambiguous, fast-moving environments and have a track record of delivering.

• Location: San Francisco Bay Area ideal. Remote considered for strong candidates, with proximity to US time zones.