Agentic Operator

About the Role

Most growth teams don't lack ideas. They lack the infrastructure to test them fast enough to matter.

We're hiring an Agentic Operator whose core output is one thing: reducing the time between hypothesis and signal. You'll build the agent pipelines, orchestration layers, and automation systems that let our growth team run more experiments in parallel — and learn from them faster — than any traditionally-staffed team could.

This is a builder role. You'll treat AI agents as a programmable workforce, replacing human bottlenecks in the experimentation loop with systems that pre-validate, instrument, execute, and surface insights automatically. You won't be handed a playbook. You'll write it in code. You'll report to the Director of Demand Generation and work closely with channel owners, lifecycle, product, and sales to make the growth team's experiments faster, more rigorous, and more evidence-based.

The right person is operationally sharp with genuine growth instincts. You understand B2B SaaS funnels well enough to prioritize experiments intelligently and catch flawed hypotheses before they waste the team's time. You're technically fluent enough to build AI workflows, instrument experiments, and own the tracking systems the team depends on. And you bring the organizational discipline to manage a high-velocity experiment backlog without letting things slip through the cracks.

What You'll Build

Agent Pipelines for Concept Pre-Validation

Before human resources touch a test, your agents have already scored it — LLM-evaluated copy variants, synthetic audience testing, funnel drop-off analysis. Only the strongest hypotheses make it to execution.

An Automated Experiment Queue

You own the full loop: intake, prioritization, instrumentation, and readout — all accelerated via automation. Funnel drop-off doesn't trigger a Monday meeting; it triggers the next test.

An Experimentation Process

You own the full loop — backlog, sequencing, instrumentation, and readout — with the rigor to match. Every test ships with a falsifiable hypothesis, clean measurement setup, and defined success metric. Null results get documented, not buried. Channel owners, lifecycle, and PLG stay in sync so the team is always running the highest-leverage tests without conflicts or duplication.

Stack Orchestration

You wire together our existing tools — Amplitude, HubSpot, Clay, REO.dev and enrichment layers — so signals flow automatically into action. You integrate frontier LLMs (Claude, GPT) and workflow tools (n8n, Gumloop) into production-grade systems that improve over time.

Parallel Experimentation Infrastructure

Instead of sequential tests, you build the infrastructure to run experiments across channels simultaneously — compressing the learning cycle and multiplying the team's throughput without multiplying headcount.