GTM Systems Engineer

About this role

GTM Engineering builds and operates the intelligent systems, integrations, and automations that power Faire's GTM revenue org. We're the AI and technical backbone of GTM — accountable for the reliability, adoption, and continuous improvement of the tech stack. We're an AI-first team: we design intelligent workflows, build automation, and invest in the data foundations that make every capability we ship compound in value over time.

We're hiring a GTM AI & Systems Engineer to help build the next generation of AI and automation across Faire's go-to-market stack. This is a builder role on our GTM Engineering team — you'll design, build, and ship the agents, integrations, and workflows that take manual work off Sales and put Faire's data to work across the customer lifecycle.

You'll work across Salesforce, sales tools, and our growing AI/MCP tooling layer, partnering closely with RevOps, Sales, GTM Program Management, and Data & Backend Engineering to find the highest-leverage opportunities and turn them into systems people actually use. Every decision about what we build is made with an AI-first lens: agent before automation, automation before manual.

Why this seat

• Wide latitude on the automation and AI layer — you'll help pick the highest-leverage problem, build it, and own how it runs, rather than execute a roadmap set for you.
• A direct line from your work to a number the business feels: rep hours saved, pipeline surfaced, faster response times.
• AI tooling as a first-class part of the job, not a side project you have to justify.

What you’ll do

• Design, build, and ship AI agents and automations across the GTM motion: lead routing and scoring, account enrichment, sequencing and outbound support, deal support, and customer lifecycle signals.
• Own and extend core parts of our Salesforce and GTM systems architecture alongside the rest of the GTM Engineering.
• Contribute to Salesforce governance and DevOps hygiene as part of keeping the stack secure, reliable, and audit-ready.
• Partner with our PAE team on the GTM data layer — Snowflake, Hightouch, Fivetran, Airflow, or related data tools — so usage and lifecycle signals reach the right system and trigger the right action automatically.
• Partner with Sales, Success, RevOps, and Program Management to find where AI and automation create the most leverage, and turn that into working, adopted systems — not just proofs of concept.
• Stand up evals, monitoring, and guardrails so every AI capability we ship is observable, reversible, and measured against a real business metric — pipeline influenced or rep time saved, not just uptime.
• Set the bar for how AI shows up in Faire's GTM motion day to day — the data-quality standard, the review points, and the guardrails other builders on the team follow.
• Help shrink the team's own keep-the-lights-on burden by identifying recurring operational work that's a good candidate for agent handling.
• Track the AI and automation tooling landscape and bring the best of it into how Faire's GTM org operates.

Qualifications

• 5+ years building automation, integrations, or tooling in a GTM, RevOps, or Business Systems context, with systems you've shipped and currently operate in production.
• Hands-on Salesforce experience (declarative, Apex/SOQL, DevOps) and working familiarity with the modern GTM stack (ETL, Reverse ETL, Snowflake, Clay, Gong, GitHub).
• Production experience with integration/automation tooling — Workato, Zapier, n8n or similar iPaaS/MCP/agent-builder platforms.
• Working fluency with AI tooling — LLM APIs, agent/orchestration frameworks, prompting with agents or AI-driven workflows.
• Judgment about where AI and automation genuinely help versus where they create risk — you know when to push automation further and when to pull back, and when to keep a human in the loop.
• Comfort with SQL and enough Python or scripting to build and debug your own pipelines and integrations.
• A builder-operator mindset: you'd rather ship something small and real than plan something big and theoretical, and once it's live, you keep making it better.
• Strong written communication — you can explain what a system does and why to both engineers and go-to-market stakeholders.

Nice to have

• Experience with BI, Snowflake, dbt, or other modern data warehousing tools.
• Experience building or extending MCP servers or agent frameworks.
• Comfort building lightweight internal tools or apps that give reps or ops a simple interface into a system.

Salary Range

San Francisco: the pay range for this role is $174,500 to $240,000 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.