Responsibilities

• Own the operating layer for marketing's agent fleet end to end — provisioning, output verification, monitoring, alerting, and incident response. Nothing counts as shipped until it has run for real and its output has been checked.
• Design and build agentic processes, skills, and automations that remove manual work from the team, and decide — with marketing judgment — which are worth building at all.
• Instrument what we build so usage, output, and value are visible to leadership, and so agents improve from feedback rather than staying frozen at launch.
• Consolidate how core marketing concepts are defined across tools and agents — territory, lead scoring stages, MQL and MQA, pipeline stages, targets — so automations and dashboards cannot quietly disagree, including across two product lines.
• Own the MarTech stack — configuration, administration, and integration — and build in a way the campaign execution team can extend without engineering support for routine work.

Requirements

• Prior marketing or marketing operations experience — required, not preferred. You already understand funnel and attribution logic, lead scoring, send-cadence and deliverability norms, and list hygiene and consent rules. This role has no downstream reviewer for marketing correctness.
• You have personally operated something unattended. A pipeline, integration, or agent that ran on its own, broke without telling you, and taught you to verify output rather than trust a green status. Scale matters less than the scar tissue.
• A track record of building production automation inside a GTM function — Clay, Zapier, Workato, n8n, or similar — where what you built was depended on by other people and you were the one who owned it.
• Evidence you have moved from no-code stitching into code and repository practice: version control, code review, CI, testing, and deploying into a shared repo rather than a personal account.
• Technical baseline: working proficiency in SQL and Python, solid REST API fundamentals, familiarity with secrets management for credentials and API keys, enough data-warehouse fluency (for example BigQuery) to query and reason about data models, and hands-on administration of HubSpot and Salesforce.

Preferred

• Direct experience with Claude, or with n8n.
• Experience building multi-step enrichment waterfalls in Clay or similar that others depend on.
• Exposure to observability or data-quality practices — monitoring, alerting, freshness and anomaly checks — in any prior role.
• Experience supporting more than one product line, where the same metric has to be correct in two motions at once.