Staff AI Product Engineer | REMOTE

AI is at an inflection point for enterprise use, and AI assistants like Claude, Codex, and Grok are seeing record adoption at work. We believe the system of record has never been more valuable for organizing the data AI acts on.

We started with our AI Order Agent, now rolled out across our customer base, which lets buyers submit orders from any source in any format. It's the first piece of a much bigger agentic ecosystem we’re building, and we're moving most of our engineering effort to AI-first work to build it.

You'll own the architecture and technical direction of our AI product suite, partnering with our Director of AI Engineering, including:

• Agentic harness: a multi-agent system that safely operates across a business's core tools (ERP, CRM, spreadsheets, calendars, email, analytics, compliance systems)
• MCP: our MCP that connects Distru to external AI harnesses
• Context Layer: our context layer that ingests customer data, builds memories and profiles, and feeds back into our harness to create more personalized AI experiences for our customers
• Evals: the eval suites that make our agents reliable in production
• And more…

You’ll be working directly on the AI system from the ground up and make strong, opinionated calls on the agentic stack and where it goes next. The AI space moves fast and the specifics will change, so this technical vision is something you'll mold.

You'll report to the VP of Engineering and the Director of AI Engineering, and work closely with the rest of the product team, eng team, and our customers.

• You've shipped core improvements to our harness in production that our customers use daily, with clear observability and iteration for improvement
• You’ve shipped and iterated on many MCP tools and improvements
• Every agent you own has an eval suite and observability, so the team catches regressions before customers do
• You own the architecture of the agentic stack, and other engineers build against patterns you set
• You’ve built prototypes on how our agentic infrastructure can improve (i.e. a new way to retrieve memories, an agentic onboarding process for our customers)
• You’ve raised the technical bar on at least one thing the team was doing the slow way

What we look for AI fluency

For every AI role, we look for three things

• Tool fluency: you build with Claude Code or similar every day, you've built your own skills, agents, or workflows, and you can explain why your setup looks the way it does.