Note: The job is a remote job and is open to candidates in USA. TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. The Marketing Technology Engineer owns the automation and AI layer of the marketing technology stack, building and operating agents, automations, monitoring, integrations, and shared marketing data definitions. The role also administers the MarTech stack and ensures marketing systems produce reliable, measurable outputs.
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
Skills
- 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
- 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
- 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
Benefits
- Distributed-first company
Company Overview
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