Agentic Operator, Growth Marketing

CircleCI

1d•$118,500 - $171,000•Remote

About The Position

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.

Requirements

Deep understanding of acquisition funnels, CRO, CAC/LTV, and hypothesis-driven testing.
Experience shipping multi-agent workflows in production.
Fluency in API-based orchestration, prompt engineering, and building self-improving feedback loops.
Experience building internal tooling that other teams depended on.
Systems thinking approach to design for leverage, considering bottlenecks, scalability, and loop closure.
Comfort operating in zero-to-one environments where defining the process is necessary.
Experience managing or coordinating a multi-stakeholder experimentation program.

Nice To Haves

Ability to describe a specific experiment cadence driven by automation.
Instinct to build solutions when hitting bottlenecks.
Prioritization of growth hypotheses over tech stack considerations.

Responsibilities

Build agent pipelines for concept pre-validation, including LLM-evaluated copy variants, synthetic audience testing, and funnel drop-off analysis.
Create an automated experiment queue for intake, prioritization, instrumentation, and readout.
Own and manage the full experimentation process, including backlog, sequencing, instrumentation, and readout, ensuring falsifiable hypotheses, clean measurement setup, and defined success metrics.
Orchestrate the tech stack, wiring together tools like Amplitude, HubSpot, Clay, REO.dev, and enrichment layers, and integrating LLMs (Claude, GPT) and workflow tools (n8n, Gumloop).
Build infrastructure for parallel experimentation across channels to compress learning cycles and multiply team throughput.