Gtm Engineer, Marketing Operations AI Innovation

Toast Toast · Enterprise · United States · Remote · Marketing : Demand Generation

This role focuses on building AI-powered agents, automations, and workflows for marketing teams within Toast. The engineer will design, build, and deploy these systems, create evaluation frameworks, and coach marketers on AI integration. The role emphasizes hands-on building and enabling non-technical users.

What you'd actually do

  1. Identify high-leverage marketing workflows and build working solutions — agents, automations, and AI-powered tools — tailored to each team's processes.
  2. Design, build, and deploy custom AI agents and agentic workflows that integrate AI APIs, MCP servers, and automation platforms into our GTM motion.
  3. Build evaluation frameworks to measure agent quality, accuracy, and reliability — including prompt evals, agent benchmarking, and regression testing.
  4. Coach marketers through a progressive AI journey: from first win, to regular integration, to full workflow transformation, to self-sufficiency.
  5. Recognize patterns and scale what works — think in reusable systems, not one-off solutions.

Skills

Required

  • 8+ years in growth marketing, product management, systems, or operations, including 2+ years in GTM Engineering, AI Engineering, or Solutions Engineering.
  • Agent building: Demonstrated experience designing, building, and deploying AI agents and agentic workflows that transformed real work — not just using AI, but building with it.
  • Evaluations: Experience building eval frameworks for AI systems — prompt evals, output quality scoring, agent benchmarking, and testing against ground truth or human baselines.
  • Fine-tuning: Practical experience fine-tuning language models for production use cases.
  • Builder mindset
  • Strong communicator who can translate technical concepts for non-technical audiences and coach different learners.
  • Track record of enabling others to permanently change how they work.
  • Growth ownership mindset
  • Hands-on with AI APIs and agent frameworks (e.g., OpenAI, Anthropic/Claude, Gemini, LangChain, CrewAI, RAG, MCP).
  • Demonstrated Clay experience
  • Familiar with martech stacks (automation tools, CDPs, CRMs, data warehouses).

Nice to have

  • Working knowledge of web services APIs and cloud services (AWS, GCP or Azure).
  • Experience with scripting languages such as Python and JavaScript - basic understanding of common syntax, able to interact with generative coding models, and debug API integrations.

What the JD emphasized

  • Agent building: Demonstrated experience designing, building, and deploying AI agents and agentic workflows that transformed real work — not just using AI, but building with it.
  • Evaluations: Experience building eval frameworks for AI systems — prompt evals, output quality scoring, agent benchmarking, and testing against ground truth or human baselines.
  • Fine-tuning: Practical experience fine-tuning language models for production use cases.

Other signals

  • building AI-powered agents
  • design, build, and deploy custom AI agents and agentic workflows
  • build evaluation frameworks to measure agent quality