Senior GTM Engineer, SentinelOne

• 6 or more years across growth/GTM marketing, marketing/revenue operations, systems, or solutions engineering, including hands-on time building automation or AI into real GTM work
• Demonstrated experience designing, building, and deploying AI agents and agentic workflows that changed real work, not just using AI tools but building with them
• Fluency with the modern GTM stack and how data moves through it (CRM, marketing automation, enrichment, outreach, analytics), and comfort owning integrations and pipelines between them
• Strong prompt architecture skills and practical experience with agent frameworks, orchestration platforms (e.g., n8n, Make), and API/MCP integrations
• Working proficiency in at least one of SQL, Python, or JavaScript, enough to build lightweight tools, integrations, and workflows
• A builder's instinct paired with GTM judgment: you understand funnels, ICP, and buying signals, and you decide what is worth automating based on revenue impact, not novelty

Desirable

• Speed up lead response. Build automations that route, score, and respond to inbound leads in minutes, not days. Own the systems behind speed-to-lead
• Build inbound AI agents. Design and deploy chat agents, form-follow-up agents, and lead-qualification agents that work the top of the funnel around the clock
• Personalize the conversion path. Build and integrate website personalization, dynamic forms, and content recommendations tied to visitor intent and account data
• Own the lead lifecycle stack. Integrate marketing automation, CDP, enrichment, intent data, and CRM so a lead's data and status stay accurate at every handoff (e.g., Marketo/HubSpot, Salesforce, Segment, ZoomInfo/Clearbit, 6sense)
• Automate content and SEO ops. Build workflows that support content production, on-page optimization, and performance tracking at scale
• Make quality measurable. Build evals for lead-scoring accuracy, chat agent quality, and routing correctness against human baselines
• Build the guardrails. Implement human-in-the-loop review for anything customer-facing, plus logging and rollback paths
• Coach and document. Bring marketing ops and demand gen up the AI curve. Build playbooks and reusable templates
• Ramp across a clear arc: in months 1 to 3, embed with one or two priority teams, map their highest-friction workflows, and ship your first end-to-end automation with a real evaluation harness behind it; in months 4 to 6, expand to additional use cases, stand up reusable templates and a shared prompt and skill library, and start coaching the teams you have served toward running things themselves; in months 7 to 12, own a meaningful slice of the GTM stack and its agentic workflows, demonstrate measurable impact in cycle-time, output quality, and capacity, and hand off matured systems to their owning teams
• Own the year-one outcome: several of the highest-friction workflows in the teams you support running on systems you built and instrumented, those teams increasingly self-sufficient, a growing library of reusable and documented templates others build on, and provable quality, with an evaluation behind every deployed system and a rollback path in front of it