Minerva Applied AI Engineer for Internal Systems at Minerva builds AI agents to automate internal company workflows. Owns the company's knowledge agent and automates processes like hiring, onboarding, and contract renewals.
Responsibilities
We build agents for marketers. This seat builds them for us.
Every company our size runs on work nobody sees. Someone copies a new hire's details into six tools. Someone remembers which contract renews next month. Someone answers the same security questionnaire for the fourth time. Most companies hire a coordinator for that work. We're hiring an engineer.
You're a forward-deployed engineer for Minerva itself. Other companies call this an AI operations engineer or an internal AI engineer. Your customers are every team here: operations, finance, people, recruiting, sales and the founders. You sit with them, find the work they'd most like to stop doing, and replace it with a system that runs without them and leaves an audit trail.
You report to our COO and work closely with engineering, which owns anything that touches production.
Own the company's knowledge agent. One agent over our docs, Slack, calls and tickets, with Slack as the front end. It answers with sources, and people trust it.
Automate the processes that run the company. Hiring, onboarding and offboarding, access provisioning, vendor reviews, customer security questionnaires, contract renewals and billing. Start where the hours or the risk are highest.
Run the skill library. Every team gets Claude connected to the tools it uses and a set of skills, each with a named owner on that team, an eval and the right permissions. What one person figures out, everyone gets.
Own the source of truth. Decide where each kind of information lives, move it there and keep it findable by people and by agents. When an agent spots something out of date, it proposes the fix and a person approves it.
Build the plumbing under our operating dashboards: the metrics, controls and board reporting that today get stitched together by hand from five systems.
Put the guardrails in first. Least-privilege access, a human approval before any agent writes to a system of record, and audit trails that double as compliance evidence.
Sit with your users. Watch how a recruiter, a seller or our finance lead actually works, then automate the part they hate.
Measure adoption. Which systems get used, by whom and at what cost, including what we spend on models and which agents can touch what. Retire what nobody opens, and write the runbook for what stays.
Qualification
An IT helpdeskProduct engineeringAn AI strategy roleThe owner of the work you automateWHAT SUCCESS LOOKS LIKE
Preferred
You've rolled out Claude or another model platform to a whole company: access, permissions, usage and cost.
You've been through a SOC 2 or similar audit on the side that produces the evidence.
Hands-on time with the systems a startup runs on: HRIS, ATS, CRM, billing and spend tools.
An IT helpdesk. You'll automate the tickets away, not answer them.
Product engineering. Our customer-facing agents and production infrastructure belong to the engineering team.
An AI strategy role. You ship systems people use. Nobody here needs a deck about transformation.
The owner of the work you automate. Our compliance lead still owns the security answers, and whoever runs sales ops owns the CRM. You build the systems that do the work for them.
