Job description

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. What You'll Bring Growth Fundamentals You understand acquisition funnels, CRO, CAC/LTV, and hypothesis-driven testing deeply enough to know which experiments are worth building for. Instinct for what moves the needle isn't optional — it's the filter on everything you automate. Agentic Build Skills You've shipped multi-agent workflows in production, not just personal automation scripts. You're fluent in API-based orchestration, prompt engineering, and building feedback loops that self-improve. You've built internal tooling that other teams depended on. Systems Thinking You design for leverage. Before touching a tool, you ask: what's the bottleneck, what happens if this scales 10x, and where does the loop close? You build things that get smarter over time. Zero-to-One Comfort The playbook for this role doesn't exist yet. You've operated in environments where you had to define the process, not just follow it — and you preferred it that way. You want the opportunity to build, improve, and adapt a new experimentation motion. Multi-stakeholder Management Experience managing or coordinating a multi-stakeholder experimentation program — not just running your own tests, but helping a team run better ones. You Might Be a Fit If… You can describe a specific experiment cadence you drove — e.g., "we went from 3 tests/month to 18" — and walk through exactly what you automated to get there Your first instinct when hitting a bottleneck is to build something, not escalate it You think about your tech stack second and your growth hypothesis first CircleCI is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. United States Base Pay Range $118,500 — $171,000 USD We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. About CircleCI CircleCI is the world’s largest continuous integration/continuous delivery (CI/CD) platform, and the hub where code moves from idea to delivery. As one of the most-used DevOps tools - processing more than 3 million jobs a day - CircleCI has unique access to data on how the most effective engineering teams work, and the tools to help software companies successfully leverage the power of AI into their commercial applications. Companies like Hinge, HuggingFace, and Samsung use us to improve engineering team productivity, release better products, and get to market faster. Founded in 2011 and headquartered in downtown San Francisco with a global, remote workforce, CircleCI is venture-backed by Base10, Greenspring Associates, Eleven Prime, IVP, Sapphire Ventures, Top Tier Capital Partners, Baseline Ventures, Threshold Ventures, Scale Venture Partners, Owl Rock Capital, Next Equity Partners, Heavybit, and Harrison Metal Capital. CircleCI is an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. How CircleCI Uses AI in Hiring At CircleCI, people make our hiring decisions. We use technology to support our recruiting team so they can spend more time on what matters most: getting to know you. Where we may use AI Job descriptions and messaging : AI may help draft job descriptions and role-specific messaging so they are clear and accurate. Application review : For some roles, we use an AI tool to review applications, including resumes and application responses, against criteria our hiring team sets for the role. The tool generates a fit score and summary to help recruiters organize and prioritize applications. Interview notes : With advance notice, an AI note-taking tool may join interviews to record, transcribe, and summarize the conversation. This lets interviewers focus on talking with you. You will be told before each interview, and you may opt out at any stage by letting your recruiter know. If you opt out, the tool will not join, and your candidacy is not affected. Outreach : AI may help draft candidate outreach and scheduling messages, which our team reviews before sending. Our commitment AI does not make hiring decisions at CircleCI. Our recruiters and hiring teams review candidates and make every decision to advance or reject an application. No candidate is rejected based solely on an AI score. We have tools and processes in place to test for bias and to review how these tools perform, and we adjust our approach as AI technology and the laws that govern it change. Your choices You can ask for human-only review of your application, opt out of AI interview note-taking, request an accommodation, or ask questions about how we use AI. Contact recruiting@circleci.com . For how we handle your data, including retention, see our Privacy Policy.

Requirements

Must-haves

Most growth teams don't lack ideas. They lack the infrastructure to test them fast enough to matter.
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
Stack Orchestration
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.
Growth Fundamentals
Agentic Build Skills
Systems Thinking
You design for leverage. Before touching a tool, you ask: what's the bottleneck, what happens if this scales 10x, and where does the loop close? You build things that get smarter over time.
Zero-to-One Comfort
Multi-stakeholder Management
Experience managing or coordinating a multi-stakeholder experimentation program — not just running your own tests, but helping a team run better ones.
You Might Be a Fit If…
You can describe a specific experiment cadence you drove — e.g., "we went from 3 tests/month to 18" — and walk through exactly what you automated to get there
Your first instinct when hitting a bottleneck is to build something, not escalate it
You think about your tech stack second and your growth hypothesis first
CircleCI is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmapici/cd

Platform: greenhouse
Effort: quick