GTM Engineer, Marketing Operations AI Innovation

Toast
RemotePosted 27 March 2026

Job Description

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. The Marketing Operations team is looking for a GTM Engineer, AI Innovation to be embedded directly with marketing teams — building AI-powered agents, automations, and workflows that permanently transform how marketers execute. You'll build alongside the people you support, measuring success by workflows transformed and teams reaching self-sufficiency. This role is open to remote candidates. A day in the life (Responsibilities) Identify high-leverage marketing workflows and build working solutions — agents, automations, and AI-powered tools — tailored to each team's processes. Design, build, and deploy custom AI agents and agentic workflows that integrate AI APIs, MCP servers, and automation platforms into our GTM motion. Build evaluation frameworks to measure agent quality, accuracy, and reliability — including prompt evals, agent benchmarking, and regression testing. Coach marketers through a progressive AI journey: from first win, to regular integration, to full workflow transformation, to self-sufficiency. Recognize patterns and scale what works — think in reusable systems, not one-off solutions. Own build-vs-buy decisions from business case through implementation. Prepare teams for an agentic future: designing, building, and overseeing multi-agent workflows. Create documentation, playbooks, and reusable templates that the entire team can leverage. What you'll need to thrive (Requirements) 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 — you'd rather ship a working POC today than present a deck about what's possible next quarter. 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 — executes end-to-end without constant guidance. 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).. Special Sauce* (Nice to Haves) 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. AI at Toast At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture. Our Total Rewards Philosophy We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more ab ... (truncated, view full listing at source)
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