We're looking for an AI Engineer to build and maintain the layer that connects us to the agentic AI ecosystem: our own infrastructure tooling (including MCP, CLI, skills), integrations across frameworks, orchestration,and data platforms, and the apps and demos that show the developer community what's possible.
It's a hands-on engineering role with real strategic weight, sitting at the intersection of marketing and product. You'll have autonomy, direct exposure to business leadership and strategic partners, and you'll be working at the actual edge of agentic AI – consistently ahead of where the broader community lands.
Responsibilities
Build and maintain our agentic infrastructure: MCP server, CLI, and skills distribution
Build and maintain integrations across the AI stack, including LangChain, LangGraph, LlamaIndex, CrewAI, Snowflake, Databricks, and more
Own our presence inside coding agents (Claude Code, Codex, Copilot, Cursor) – tracking recommendation rates, producing reports, and aligning with product and leadership
Build apps and agents that show the AI community what's possible with us
Publish technical content, from feature release to newsletters and strategic docs.
It's a hands-on engineering role with real strategic weight, sitting at the intersection of marketing and product. You'll have autonomy, direct exposure to business leadership and strategic partners, and you'll be working at the actual edge of agentic AI – consistently ahead of where the broader community lands.
Responsibilities
Build and maintain our agentic infrastructure: MCP server, CLI, and skills distribution
Build and maintain integrations across the AI stack, including LangChain, LangGraph, LlamaIndex, CrewAI, Snowflake, Databricks, and more
Own our presence inside coding agents (Claude Code, Codex, Copilot, Cursor) – tracking recommendation rates, producing reports, and aligning with product and leadership
Build apps and agents that show the AI community what's possible with us
Publish technical content, from feature release to newsletters and strategic docs.
Requirements:
2+ years building production LLM systems that real customers depend on
Strong Python; hands-on experience with leading agentic frameworks (e.g. LangChain)
Deep familiarity with MCP (at the level of reasoning about tool surface tradeoffs, not just experimentation)
Experience optimizing agent performance, e,g. token efficiency, context management, and latency
Someone who moves without a fully scoped spec and thinks about both technical and market impact
Excellent written English, technical and marketing alike.
2+ years building production LLM systems that real customers depend on
Strong Python; hands-on experience with leading agentic frameworks (e.g. LangChain)
Deep familiarity with MCP (at the level of reasoning about tool surface tradeoffs, not just experimentation)
Experience optimizing agent performance, e,g. token efficiency, context management, and latency
Someone who moves without a fully scoped spec and thinks about both technical and market impact
Excellent written English, technical and marketing alike.
This position is open to all candidates.
