Senior AI Engineer
## Our stack
You should be strong across most of this.
- Agent frameworks: LangGraph / LangChain — building agents, subagents, and orchestrated subagent fleets.
- Frontend: React, React Native.
- Backend: Node.js.
- Models (we're model-agnostic): Claude / Anthropic, OpenAI / Codex, DeepSeek, Gemini, Sakana — routing across multiple models per task.
- Agent infrastructure: MCP servers, subagent orchestration, short-term and long-term memory systems.
- Data: integrating external data sources into agents; synthesizing unstructured/structured data into models; scraping (bonus).
- Domain (preferred): blockchain data, blockchain RPC, stablecoins.
## The role
You'll lead the design and delivery of our most important consumer AI features — owning the architecture, quality, and roadmap of how AI shows up in the product. You'll set technical direction, mentor other engineers, and be the person who makes hard applied-AI problems ship reliably at scale. This is an applied product role, not a research or protocol-engineering role.
## What you'll do
- Own end-to-end design and delivery of consumer-facing AI features, from concept to production.
- Architect robust agent systems with LangGraph / LangChain: agents, subagents, and orchestrated subagent fleets.
- Design and build MCP servers and the tooling that connects agents to the rest of the product.
- Build short-term and long-term memory systems and integrate external data sources into the agent fleet.
- Route intelligently across multiple AI models (Claude, OpenAI / Codex, DeepSeek, Gemini, Sakana) based on task, quality, latency, and cost.
- Build the eval and observability foundations that let the team ship quality improvements with confidence.
- Set technical direction for applied AI and mentor junior and mid-level engineers.
- Partner with product and leadership to shape what we build and why.
## What we're looking for
- 5+ years of software engineering experience, with a strong track record of shipping consumer-facing products to real users at scale.
- Demonstrated experience building applied AI / LLM-powered features in production — not just experiments.
- Deep fluency in TypeScript/Node.js and/or Python; experience with React and/or React Native.
- Hands-on experience building agents and subagents, including subagent orchestration and MCP servers.
- Experience working across multiple model providers and routing between them.
- Experience integrating external data sources into agents for short-term and long-term memory.
- Experience designing evals and improving model-driven systems with data.
- Strong product instincts: you make good trade-offs between speed, quality, cost, and UX.
- Ability to lead projects and level up the engineers around you.
## Nice to have
- Strong at scraping unstructured data and turning it into something an agent can use.
- Experience with blockchain data, blockchain RPC, and stablecoins.
- Experience in crypto, fintech, or payments, ideally on consumer products.
- Experience scaling AI features under real latency, reliability, and cost constraints.
- History of taking 0→1 products to launch.
As part of the screening process, please kindly include the following at the bottom of your resume/application:
1. Your top two favorite products
2. One of your favorite apps and one of your favorite brands, with a brief explanation of why you like them
3. A URL link to your portfolio
Please note that applications with this information will be preferred over those without.