Faire1 день назад
GTM Systems Engineer
Зарплата не указана
San Francisco
Обязанности
- 01Design, 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
- 02Own and extend core parts of our Salesforce and GTM systems architecture
- 03Contribute to Salesforce governance and DevOps hygiene as part of keeping the stack secure, reliable, and audit-ready
- 04Partner 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
- 05Partner with Sales, Success, RevOps, and Program Management to find where AI and automation create the most leverage, and turn that into working, adopted systems
- 06Stand up evals, monitoring, and guardrails so every AI capability we ship is observable, reversible, and measured against a real business metric
- 07Set 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
- 08Help shrink the team's own keep-the-lights-on burden by identifying recurring operational work that's a candidate for agent handling
- 09Track the AI and automation tooling landscape and bring the best of it into how Faire's GTM org operates
Требования
- 015+ years building automation, integrations, or tooling in a GTM, RevOps, or Business Systems context, with systems you've shipped and currently operate in production
- 02Hands-on Salesforce experience (declarative, Apex/SOQL, DevOps) and working familiarity with the modern GTM stack (ETL, Reverse ETL, Snowflake, Clay, Gong, GitHub)
- 03Production experience with integration/automation tooling — Workato, Zapier, n8n or similar iPaaS/MCP/agent-builder platforms
- 04Working fluency with AI tooling — LLM APIs, agent/orchestration frameworks, prompting with agents or AI-driven workflows
- 05Judgment about where AI and automation genuinely help versus where they create risk
- 06Comfort with SQL and enough Python or scripting to build and debug your own pipelines and integrations
- 07A 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
- 08Strong written communication — you can explain what a system does and why to both engineers and go-to-market stakeholders
Условия
- 01Salary Range San Francisco: $176,000 to $242,000 per year
- 02This role will also be eligible for equity and benefits
- 03Hybrid work model: 3 days per week in office (Tuesdays, Thursdays, and a third flex day)
- 04Flexibility to work remotely up to 4 weeks per year