This is a builder role for someone who wants to work at the edge of applied AI.
You will work directly with operators, business owners, and internal subject matter experts to understand how a company actually runs, then turn that understanding into working AI systems.
That might mean building an agent that reviews inbound requests, pulls context from multiple systems, drafts the right response, routes approvals, updates the CRM, creates follow-up tasks, and escalates exceptions to the right human.
It might also mean building the boring but critical pieces around the agent: data pipelines, tool integrations, retrieval systems, evaluation loops, human review queues, audit trails, permissions, and monitoring.
What You’ll Do
You will design and build AI agents, internal tools, workflow engines, automations, and integrations for mid-market companies.
You will work with client teams to understand real business processes, not sanitized diagrams.
You will connect AI systems to the tools companies already use: CRMs, ERPs, email, Slack, Google Workspace, Microsoft 365, databases, spreadsheets, ticketing systems, and vertical SaaS platforms.
You will build prototypes quickly, test them with real users, and turn the useful ones into production-grade systems.
You will design human-in-the-loop workflows where AI drafts, recommends, routes, summarizes, researches, classifies, or executes — but humans remain in control where judgment matters.
You will create systems that handle edge cases, bad data, missing context, permission issues, unclear ownership, and the weird “this is just how we do it” logic that exists inside every company.
How We Work
We move fast.
We get close to the business.
We ask annoying questions until the real constraint is obvious.
We prototype quickly, ship carefully, and improve based on how people actually use the system.
We believe AI implementation is not about replacing teams. It is about giving teams better systems, better leverage, and less manual drag.