GTM Engineer

Builds with AI assistants and agent frameworks to automate GTM; heavy on agent-assisted workflows, rapid AI-driven experiments, and tooling. About the Role SageOx is hiring a GTM Engineer based in Seattle to build and run the demand engine for an early-stage AI product. The role combines hands-on engineering of AI-powered automation with content, community, outbound, and experimentation to drive qualified signups and measurable customer traction. Job Description Role SageOx is seeking a GTM Engineer to own the full customer-to-product learning loop and build the machinery that drives demand for an early-stage AI product. This hands-on role combines technical execution, content and community growth, outbound systems, and repeatable experiments to generate qualified signups and measurable traction. Key Responsibilities Own customer and market learning: talk to founders, engineers, product teams; map tools, communities, workflows, and search behavior around the ideal customer. Be the tip of the spear for market feedback: engage in social and community channels and surface outside-in signals to product and engineering. Run content and voice: publish regular posts, threads, short video, tutorials, demos, case studies, and positioning inputs derived from customer insights. Amplify founders: identify high-impact platforms, secure opportunities, and connect founders to target audiences. Run community marketing: launches, influencer collaborations, hackathons, event presence, and local builder community engagement in Seattle and SF. Build AI-powered GTM infrastructure: prospecting automation, lead scoring/enrichment, customer-facing utilities and demos, lightweight integrations, and MCP-based workflows. Automate the GTM stack: wire CRM, data sources, and onboarding funnels; instrument activation and conversion signals and make playbooks repeatable. Run rapid experiments: hypothesis-driven small distribution tests across communities, content, integrations, partnerships, and outbound; measure, decide, and scale or kill. Requirements 2–7 years of experience across software engineering, solutions engineering, technical marketing, or growth. Deep, hands-on fluency with AI: experience building with modern AI models, agent frameworks, and AI coding agents; use AI daily to scale work. Technical ability to build automations, integrations, MCP-based workflows, analytics, and lightweight public utilities or templates. Track record of shipping projects or growth channels (core/side projects, internal tools, hackathons, open source, or audience/funnel growth). Strong customer empathy, experiment mindset, and comfort communicating via writing, video, or practical projects. High ownership, ability to operate autonomously in an early-stage environment, and alignment with company mission and culture. Local presence required: in-person in Seattle five days a week; Bay Area candidates considered if able to be in Seattle at least two weeks per month through end of 2026. Success Metrics Qualified signups/trials sourced per week and engaged conversations that convert into customers. Number of experiments run per month with documented learnings and measurable outcomes. Inbound signups attributable to content and outbound automation; reproducible playbooks for repeatable wins. Hiring Process & Logistics No traditional interview loop: candidates clear an initial assessment and are invited to a 3–5 day work trial in Seattle working alongside the team. Compensation: competitive salary and meaningful equity (details discussed after mutual fit is established). Skills Customer Research Content Strategy Community Building Outbound Growth Experimentation Data Instrumentation & Analytics Automation Technical Communication Product Positioning Cross-functional Collaboration Ownership Customer Empathy Experience Level Mid Employment Type Full-time Bay Area candidates permitted with requirement to be in Seattle ≥2 weeks/month through end of 2026 High autonomy and early-stage influence #J-18808-Ljbffr Vibehackers