GTM Engineer - Sales Workflow Automation, Revenue Intelligence at Toast
- Pay: $94,000–$192,000 a year.
- Remote.
The GTM AI Transformation team is hiring a GTM Engineer to build the agents and automations that run inside Toast's sales motion. You'll write production code in Python against Salesforce, Snowflake, and LLM APIs, extend our sales AI platform (Myko) with custom integrations, and turn call transcripts and deal data into actions that reach reps and managers without anyone asking for them. This is a builder role. You'll own systems from prototype through production operation, and the measure of success is whether reps use what you ship and close faster because of it. You'll report to the Senior Manager of GTM AI Transformation and work day to day with sales leadership, Revenue Operations, Enablement, and Toast's Data and Engineering teams. The role is fully remote in the United States. A day in the life (Responsibilities) Agentic workflows that automate high-volume sales work end to end: follow-up drafting, deal stage updates, task creation, and Slack and CRM notifications, with approval gates and handoffs that keep reps in control. Integrations between our prospecting agents and adjacent systems (quoting, pricing, case creation) so a rep can go from signal to action without leaving their workflow. Pipelines that pull conversation intelligence transcripts into Snowflake and the CRM, and services on top of them that produce next best actions, deal risk flags, and coaching recommendations for frontline managers. The production controls around all of it: evals that catch regressions before reps see them, observability tied to pipeline and revenue outcomes, permissions and sensitive-data handling, error recovery and rollback. A third-party signal layer (intent, news, firmographic change) that flows into account prioritization, and the win/loss data capture that tells us what's working. What you'll need to thrive (Requirements) Proficiency in Python (TypeScript also works) and strong SQL. You write production-grade, tested code, and you can read, modify, and debug code you didn't write, including code generated by AI tools. At least one LLM-powered workflow or agent you built that a business team used in production, built against an LLM API (Anthropic, OpenAI, or similar) or an agent framework (LangGraph, Claude Agent SDK, or similar), with tool calling, error handling, and some form of evaluation. You'll be asked to walk through it. Hands-on Salesforce experience: data model, Flow, APIs, permissions, and what happens when an integration writes bad data at scale. Comfort working directly in a data warehouse (Snowflake preferred) for pipeline QA, transformation, and validation. Experience with REST APIs, webhooks, auth, and integration troubleshooting across SaaS systems. Typically 4 to 6+ years in GTM Engineering, Business Systems, Solutions or Forward Deployed Engineering, Data Engineering, or software engineering applied to sales or marketing. We weigh the depth of what you've shipped over the title you held. You can explain a technical tradeoff to a sales VP and a data model to an engineer in the same week. What will help you stand out (Nonessential Skills/Nice to Haves) MCP, RAG, or eval framework experience; you've thought about how to know whether an agent is getting better or worse. Salesforce Apex or Platform Developer certification. dbt or similar transformation tooling. Experience with conversation intelligence (Gong, Chorus) or sales engagement platform APIs. Enrichment and signal tooling (Clay, ZoomInfo, Demandbase) and what to do when the data disagrees. Reporting in Tableau, Looker, or Sigma. You've worked in a multi-product, multi-segment sales motion in SaaS or fintech. 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. …