Marketing AI Engineer

Responsibilities

• Map and prioritize automation opportunities: Work closely with marketing teams to develop a deep understanding of their day-to-day processes — identifying where AI agents and automated workflows can eliminate manual work, reduce errors, or unlock capabilities that weren’t previously possible.
• Design and build AI agents: Develop AI agents and automated workflows that streamline marketing processes — from content production and campaign operations to reporting, lead routing, and personalization at scale.
• Deploy and maintain automations: Own the full lifecycle of deployed agents — from initial release through ongoing monitoring, debugging, and iteration — ensuring reliability and performance as usage grows.
• Produce efficiency and impact reporting: Track and report on workflow automation metrics — time saved, error rates, throughput, and business impact — delivering regular dashboards and summaries to marketing leadership.
• Stay current on AI tooling: Continuously evaluate new AI models, agent frameworks, and automation platforms — bringing a clear point of view on what Sonar marketing should adopt, experiment with, or build on next.
• Partner with Marketing Tooling & AI Operations: Collaborate closely with the Marketing Tooling & AI Operations Manager to understand the existing tool stack, ensure automations integrate reliably with it, and drive adoption of new AI-powered capabilities.
• Ensure data quality and governance: Design automations that handle marketing data responsibly — with attention to data quality, privacy, and auditability across all deployed workflows.
• Document and enable: Produce clear documentation for all deployed agents and workflows, and run internal enablement sessions to help the marketing team understand and effectively use what you have built.

Qualifications

• Have 3+ years of experience in marketing operations, automation engineering, or a closely related role — with a track record of building workflows or automations that measurably improved team efficiency.
• Have deep, hands-on knowledge of marketing processes and tools — including CRM (Salesforce), marketing automation, campaign ops, analytics, and content workflows. A marketing ops practitioner who has grown into building automations is a strong fit.
• Be experienced with no-code/low-code automation platforms (e.g., Make, Zapier, n8n) and comfortable extending them with scripting when needed (Python and/or JavaScript).
• Have working familiarity with AI agent frameworks (e.g., LangChain, Claude Agent SDK, OpenAI Assistants) or a demonstrated ability and appetite to ramp quickly.
• Be experienced integrating with third-party APIs and working with marketing data structures (e.g., Salesforce, HubSpot, GA, Marketo).
• Have strong analytical skills and experience building performance dashboards and reporting for deployed automations.
• Be a clear communicator who can explain what an automation does — and why it matters — to non-technical stakeholders, and translate their requirements into precise technical specifications.
• Bring intellectual curiosity and a bias to build — you stay current on the fast-moving AI landscape and bring that knowledge into your everyday work.
• Hold a Bachelor’s degree in Marketing, Business, Computer Science, or a related field.