Founding Revenue Operations Lead
Mintive
Founding Revenue Operations Lead
Mintive
Enterprise AI governance and security platform
Mintive helps companies put agents to work safely. We exist to help companies do more of their work with agents, and we build the infrastructure that makes a company's own work runnable by them. That has to start from trust. Our first product is an MCP gateway that gives those agents governed access to company data and tools.
Before agents can touch Slack, GitHub, Jira, Snowflake, internal databases, or production systems, you need to know what they can reach, what they did, and why they were allowed to do it. Most people carry far more permissions than any single task needs. If an agent uses your token directly, it inherits all of them. Our gateway product scopes that access down to exactly what an agent needs to do its job and captures the data flows and audit logs security teams need. From there we are building the rest of the agent stack: connectors, monitoring, sandboxing, long-running agents, and memory, with the goal of becoming the system a company's work runs on.
We're hybrid, the structure is flat, and the market moves fast, so you have a lot of latitude over what you work on and how.
We are AI-native. Everyone uses Claude and Codex every day, and we have more agents than employees. They run in Slack alongside the team and handle sales, marketing, deal ops, and engineering on the same gateway we sell to customers, and we are building an entire company operating system around them.
Since launching in February 2026, we have grown to 50+ paying customers, with strong inbound demand. Customers include Coursera, Arlo, and Braze. We are backed by Cowboy Ventures and Coatue, with angels including Frederic Kerrest (Okta), Michael Grinich (WorkOS), Andrej Karpathy, Jeff Dean, and Scott Belsky. Our founders are machine learning experts from Stanford, Berkeley, and CMU, with applied research at Google Brain and Waymo, and one co-founded Coursera.
Mintive is growing fast and opening new go-to-market motions at the same time, and we want to do it with a small, efficient team, which means we can't hire our way there. The engine has to do the work. You'll build it: the data, systems, and agents that make every rep, partner, and motion dramatically more productive, and you'll keep rebuilding it until it's 10x what it is today. You report to and work directly with the Head of Revenue, close enough to shape decisions before they're made. You'd rather build the machine than feed it, and you'd rather the machine act than report. The role is hybrid in the Bay Area, out of our San Francisco and/or San Mateo offices.
Map every workflow, then automate the biggest ones away. Inventory everything we run across marketing, sales, support, finance, and alliances: automated, agentic, manual, or not done at all. Rank it by revenue impact and hours burned, then ship agents and automations against the top of the list. Every manual step is a candidate for deletion.
Build agents that do the work, not describe it. Agents that research and prep accounts, route and enrich leads, chase follow-ups, assemble deal reviews, flag at-risk renewals, and kick off co-sell with partners. The goal is more selling time per rep and more pipeline per head, not more dashboards.
Engineer the data foundation the engine runs on. One source of truth across marketing, sales, support, finance, and technical alliance partners, clean enough that agents can act on it without a human double-checking. Every number has an owner, a definition, and a consequence. When two teams disagree about a number, you settle it and it stays settled.
Launch every new motion with the engine built in. Every new motion, channel, and market goes live with automation and instrumentation from day one, not bolted on later. That includes partner attribution: sourced vs. influenced revenue, co-sell, and integration-led pipeline.
Turn signal into action. Leading indicators, structural risks, and pipeline shifts trigger plays automatically and route to the right owner with the next step attached, instead of waiting in a chart for someone to notice. You call the quarter early, and you'll have a view and defend it.
Year one, you'll move: rep productive capacity (selling time and pipeline per rep), and forecast accuracy at or above 95%.
In 90 days: three agents or automations live in production with measured impact (hours returned to the field, faster cycles, more pipeline), plus a ranked backlog of what's next.
You'll build with: Attio, our own long-horizon agents, Claude, OpenAI, Slack, and Google Workspace.
You've shipped real systems: an agent in production, an automation that replaced a team's busywork, a messy dataset you tamed into something machines can act on.
You measure your work in hours eliminated and revenue unlocked, not reports delivered.
You're a mid-level, exceptional builder with 4+ years in RevOps, sales ops, GTM engineering, or a similar role.
You're agent-native. You use Claude and agents to scale your own output, with the judgment to know when AI sharpens the work and when it just produces noise.
You move fast and thrive without much structure, and you add structure without adding bureaucracy.
You partner well with founders and a scaling sales team, and you can get sales, finance, and partners to agree on one number.
Familiarity with MCP, AI agents, or enterprise security and governance.
Experience spanning both self-serve/PLG and sales-led motions.
You've built partner attribution or co-sell reporting for a technical alliances or channel program.
You've been a founding or early ops hire and built the engine from zero.
Competitive base and significant equity.
Ownership of the revenue engine.
A front-row seat to agentic AI at a company that already has more agents than employees.
Direct access to our Head of Revenue, the founders, and how the company actually runs.
Health benefits, on a team that puts family and health first.
Prefer to have your agent apply? Point it at https://www.mintive.com/hiring/mcp
Mintive provides an infrastructure platform for enterprises to govern AI agents, including access control, monitoring, and cost management. Its MCP Gateway and LLM Gateway route all agent traffic to enforce tool and model permissions and block unsafe actions. Agent Identities, Agent Monitor, Mint Guard, and Coworker Agents offer identity, observability, safety, and collaboration features for autonomous agents. The goal is to enable secure, auditable deployment of AI agents at scale for security- and IT-focused teams, with customers like Coursera, Braze, Stability AI, and Eurostar, and with SOC 2 Type II compliance and custom pricing.
Explore more opportunities at Mintive