AI Ops Engineer (Marketing)

Job summary

Responsibilities

You report into Applied AI and spend most of your time with Marketing. Marketing leadership sets the priorities and owns the results. You agree with them on what to build, how to measure it, and who owns each system once it runs.

• Run a listening tour with Marketing. Map current work, systems, data sources, owners, and the places where expert judgment lives. Propose builds only after that.
• Agree each project with Marketing leadership up front: the problem, the metric, the owner, and the definition of done.
• Connect the context a launch depends on: Linear tickets, internal docs, Slack threads, competitive intel, and usage data.
• Build agents and workflows for Performance and Social: creative variants, campaign setup, and quality checks against brand guidance, with human review where spend or brand is at…
• Encode Brand and Product Marketing judgment into systems: positioning, messaging, and voice guidance that other teams and agents apply without a meeting.

What they're looking for

• 6+ years building and shipping production software or data systems that people depend on. Recent hands-on work in TypeScript, Python, or SQL.
• Deep marketing knowledge from a marketing organization, a MarTech company, or a product or data role serving marketing teams.
• Experience integrating marketing systems: ad platforms, analytics, CRM or CDP, and content tools. You know their APIs and data well enough to build on them.
• Experience building with LLMs: agents, evaluation, and the judgment to know where a rule-based system does the job better.
• Strong product judgment. You start from the problem, choose priorities with the people affected, and improve a system through use and feedback.

Tech stack

• TypeScript
• Python
• SQL
• PostgreSQL
• BigQuery