Enterprise Sales Lead, AI Data Operations

You already know the pitch. You have given it a hundred times.

You have sat across from an ML lead who was convinced their model’s ceiling was an architecture problem, and walked them through why it was actually a labeling taxonomy problem. You have priced RLHF programs. You have defended inter-annotator agreement numbers in a QBR. You know the difference between a vendor who can throw 500 annotators at a queue and one who can find 40 people who actually understand the domain.

If that is your last three years, keep reading.

Why we are hiring

Arise runs one of the largest networks of experienced customer-experience professionals in the world — people who have spent years handling real customer conversations, escalations, and edge cases across industries.

That network turns out to be exactly what the current wave of AI needs. Every lab and enterprise building conversational agents, support automation, or agentic workflows is hunting for the same thing: domain-expert humans who can generate, grade, and correct realistic interaction data at volume. Not generic crowdworkers. Practitioners.

We have the supply. We are building the go-to-market. That is this role.

What you will actually do

• Own pipeline generation. This is a build role, not an inherited-book role. You will be feet on the street in the Bay Area, working the AI ecosystem directly — labs, applied ML teams, AI platform companies, and enterprise automation buyers.
• Sell the technical work, not the logo. Data collection and annotation, human-in-the-loop QA, preference and ranking data, model evaluation and red-teaming, conversational and multimodal datasets, agent-trajectory data.
• Scope with the people who deliver it. You will work directly with operations and AI engineering to build programs that are actually deliverable — throughput, quality thresholds, ramp plans, and pricing that survives contact with a real workload.
• **Partner wit