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Faire is a technology wholesale platform connecting independent retailers globally with suppliers. The GTM Engineering team builds intelligent systems, integrations, and automations that power Faire's go-to-market revenue organization, with a focus on AI-first design and data-driven workflows.
In this role, you'll design, build, and ship AI agents and automations across Faire's GTM motion, including lead routing and scoring, account enrichment, sequencing and outbound support, deal support, and customer lifecycle signals. You'll own and extend core parts of the Salesforce and GTM systems architecture, working closely with RevOps, Sales, GTM Program Management, and Data & Backend Engineering teams.
Key responsibilities include: designing and deploying AI agents and automation workflows; maintaining Salesforce governance and DevOps hygiene; partnering on the GTM data layer (Snowflake, Hightouch, Fivetran, Airflow); identifying high-leverage opportunities for AI and automation adoption; establishing evals, monitoring, and guardrails for AI capabilities; setting standards for AI implementation across the GTM team; and reducing operational overhead through intelligent automation.
You'll have wide latitude to identify the highest-leverage problems, build solutions, and own how they run in production. Every decision is made with an AI-first lens: agent before automation, automation before manual work. Your work directly impacts measurable business outcomes—rep hours saved, pipeline surfaced, faster response times.
Required: 5+ years building automation, integrations, or tooling in GTM, RevOps, or Business Systems contexts with production systems you've shipped and operated. Hands-on Salesforce experience (declarative, Apex/SOQL, DevOps) and familiarity with the modern GTM stack (ETL, Reverse ETL, Snowflake, Clay, Gong, GitHub). Production experience with integration/automation platforms (Workato, Zapier, n8n, or similar iPaaS/MCP/agent-builder tools). Working fluency with AI tooling—LLM APIs, agent/orchestration frameworks, and AI-driven workflows. SQL proficiency and enough Python or scripting to build and debug pipelines. A builder-operator mindset focused on shipping real solutions and continuously improving them.
