Staff AI Product Engineer | REMOTE

About the role

About Distru

Distru is the #1 ERP in the cannabis industry with $15B in sales processed through our platform. We've built a battle-tested ERP and B2B eCommerce platform that powers inventory, manufacturing, sales, and logistics, and we're now building AI infrastructure on top of it to give commercial businesses their all-in-one AI stack.

We're growing and profitable , with 5/5 stars on Glassdoor . Our investors include Felicis Ventures , Global Founders Capital , Poseidon Asset Management , and Village Global , who have funded companies such as Shopify, Cruise, HelloFresh, Facebook, Slack, and Opendoor.

Get to know the team, our culture and our full benefits at distru.com/careers !

The Role

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.

What you'll do

Agentic engineering

Architect and build a production multi-agent system that can safely take actions across Distru and our customer’s core systems

Iterate and maintain the MCP that connects Distru to Claude & Codex.

Own reliability, observability, and durable execution end to end. The harness takes real actions on customers' data, so the bar is high.

Write evals to improve our agentic systems from real customer use cases

Build a unified data system that pulls data from multiple sources into a singular data layer that can be exposed to Claude & Codex via an MCP

Build a contextual memory system that ingests our customers' data and improves how our agents work for them

Set the architectural standards for how agents are built, tested, and shipped at Distru, and bring the rest of eng along

AI research & experimentation

Keep pace with the latest agentic frameworks, harnesses, toolkits, models, and bring in better approaches as they emerge

Rapidly prototype new ideas to present to our team and our customers

Engineering workflow

Build hands-on with Claude Code and similar tools as part of your own workflow

Improve our agentic coding workflow and bring new discoveries to the team

What success looks like at 6 months

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.

Workflow fluency: you write evals before you trust a prompt, and you know when a model is the wrong tool and plain code is the right one.

Build fluency: you've put agents in front of real users, with guardrails, observability, and a way to roll back.

You use AI tools daily and can tell us specifically where your fluency is strong and where you're still building it.

Must have

7+ years in full-stack development, ideally on B2B SaaS applications

Multi-agent harnesses: hands-on experience building multi-agent harnesses in production, not just prototypes or personal projects

MCPs: you've built MCPs that are used in production

Production systems: a strong grasp of reliability, observability, permissions, and safe workflow execution

Product and engineering: you've operated as both, and you're comfortable owning scoping and decisions, not just implementation

Modern stack: proficiency in React, TypeScript, Node, PostgreSQL, GraphQL, and LangGraph, and you pick up new tools and frameworks quickly

Startup agility: you've worked at an early-stage startup (under 20 engineers) and you’ve been the one setting direction in that ambiguity, not waiting for it

Low ego: you're team-first and measure success by what shipped and whether it worked, not by internal politics

Influence : you’ve shaped roadmap, not just executed it

Clear communication: you raise concerns and propose solutions before being asked

Strong signal

Background building supply chain, ERP, CRM, B2B marketplace, or accounting software

UX design experience

Agentic systems work beyond the must-haves, such as evaluation frameworks or agent-to-agent protocols

Experience using Claude Code (or similar) to build products on your own

Cannabis industry experience

How we work

We love building with AI. Trying new models the week they drop, building agents for fun, and forming strong opinions on what works. We invest in it with company-wide AI growth with classes and workshops, AI demo days, AI hackathons, and access to best-in-class models and tools.

Taste in building. A lot of this role comes down to knowing what to build, what to cut, and what a great agentic experience feels like for the user.

We stay close to the customer. You'll talk to customers and our GTM team directly, not through a chain of tickets.

You'll build on what we've learned. You'll have access to the team's combined AI knowledge and the processes and skills we've built.

For the full picture of our culture and who thrives here, see distru.com/careers .

Where you land in the range depends on your experience and skills.

Benefits

Our careers page is the best way to get to know us: the full benefits, our yearly offsites, who thrives here, and what the team says about working at Distru.

Here are a few highlights (exact benefits vary by country and employment type):

Fully remote across 4 continents

Employee-friendly option terms: after 2 years, a 10-year window to exercise if you leave

18 days PTO + 11 holidays (sick days don't count toward PTO)

Medical, dental, vision + 401(k) for US employees

The best AI tools available and a generous AI stipend for everything else

Yearly in-person team offsites

Interview process

Application questions: three short written questions in Lever on how you build with LLMs

Recruiter screen (30 min): your background, the most complex AI product you've worked on, and your personal AI tool stack

Technical interview (45–60 min): a deep dive into a complex product you've built, a live harness design discussion, and a screen-share walkthrough of your day-to-day setup

Harness take-home (3–4 hours): spec a real feature on our agentic harness across product and UX, system design, and implementation details

Take-home review (60 min): a technical deep dive into your submission with two engineers, including how your design holds up when a constraint changes

References and offer

Distru was formed by an environment of mutual respect and trust made up by people working together without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by law. We believe that diversity and inclusion among our team members is critical to our success and we proactively strive to recruit, develop and retain the best and brightest people from the most diverse candidate pools we can find all over the world.

Posting text as published by Distru.

The evidence behind this listing

Workplace

Remote Employer field

Seniority

staff+ From the job title

Employment type

full time

Location as listed

Remote, Worldwide

Pay and work authorization

Stated pay

$200k–300k/yr Employer field

Visa sponsorship

Not stated

Security clearance

Not established

Citizenship

Not established