AI Solutions Engineer

About Us
HeadQuarters is a global start-up that partners with US cannabis companies to provide support in finance, sales operations, and logistics. We are currently seeking an AI Solutions Engineer to join our growing product development team.

The Role

We're hiring an engineer to design and build AI agents and automations for our external customers in the fast growing Cannabis / CPG industry.  You'll partner with our team from the first conversation through delivery: understanding a customer's workflows, scoping what an agent should own, building it on top of their systems, and making sure it runs reliably in production. The most important part of this job is learning how a customer's work actually gets done: sitting with their frontline staff, earning their trust, and turning unwritten rules and exceptions into logic a system can follow.

Once an agent is live, you'll hand it off to one of our Operations Managers, who oversee the agent's day-to-day work and output on the customer's behalf.

Every customer runs on a different stack, so this role calls for real engineering depth, and you don't need a long AI resume to have it. We're looking for a strong developer who has recently put LLM-powered workflows into production. Plenty of people can prompt their way to a working prototype. We need someone who can own the code behind it, troubleshoot it inside an unfamiliar environment, and harden it so it holds up long after you've moved on to the next customer.

What You'll Do

Discovery and Scoping (with the AI Sales Lead)

• Join customer discovery calls to understand their workflows, systems, data, and pain points
• Sit with customers' frontline staff to learn how the work actually gets done, capture the rules and exceptions that live in people's heads, and translate them into explicit logic
• Build trust with the people whose work you're automating, and treat them as the experts on their process
• Assess technical feasibility and identify which tasks are good candidates for an agent and where human review should stay in the loop
• Translate customer needs into solution designs, effort estimates, and clear scope
• Build proofs of concept and demos that show customers what an agent can do with their own workflows
• Provide build and run cost estimates (model usage, infrastructure, maintenance) to support pricing

Build and Deploy

• Design, build, and deploy AI agents and automations that handle multi-step workflows across customer operations