GTM Engineer, Conveo AI

• 2-5 years of experience writing production code in TypeScript/Node.js, Python, or similar. You can build and ship a full-stack app end-to-end
• Hands-on experience with Supabase, Firebase, or equivalent (Postgres, serverless functions, auth, storage)
• Demonstrated experience building internal tools, automations, or data pipelines that had measurable business impact
• Comfort with LLM tooling and AI workflows: you've built with Claude, GPT APIs, or similar, not just used them
• Working knowledge of the modern GTM stack: CRM (HubSpot), analytics (GA4/GTM), marketing automation, and API integrations
• Strong communication skills: you can explain technical trade-offs to non-technical stakeholders and translate business problems into technical specs
• High agency, low ego: you see what needs to happen and you make it happen
• Builder mentality: you'd rather ship a working prototype than write a spec about it
• Commercially minded: you measure your work in business outcomes (pipeline, activation, FTEs saved), not lines of code
• Speed over perfection: you ship fast, learn, iterate. You know when "good enough" is the right call and when it isn't
• Resourceful: you can figure out any API, debug any integration, and learn any tool in a weekend

Desirable

• Conveo is scaling from 20x revenue in 2026. That kind of growth doesn't happen with manual processes and duct-taped spreadsheets. We need someone who can code, ship, and iterate on the internal tools and automations that make our GTM team dangerously effective
• Today, our GTM team runs on a patchwork of SaaS tools, manual workflows, and tribal knowledge. The opportunity: replace that with purpose-built apps, pipelines, and AI-powered workflows that compound over time
• Think lead scoring models that learn, attribution pipelines that actually work, onboarding flows that activate customers faster, and AI agents that eliminate hours of manual work every week
• This is not a traditional ops role. You write code. You ship apps. You build with tools like Claude Code, Supabase, Node/TypeScript, and modern APIs. You sit at the intersection of engineering and GTM, and you measure your work in pipeline generated, FTEs automated, and activation lift delivered
• This role reports to the CGO (Florian) and works in close partnership with Sales, Marketing, Customer Success, and Product Engineering
• You don't configure off-the-shelf tools. You build what doesn't exist yet, fast, and iterate based on what the team actually needs
• Build and ship in-house applications using Supabase (Postgres, Edge Functions, Auth, Storage), Node/TypeScript, React, and Python
• Create customer-facing and internal dashboards, portals, and workflows that eliminate manual work
• Prototype rapidly: go from problem to working POC in days, not weeks
• Own the full stack of your builds: data model, backend logic, frontend, deployment, and iteration
• Every dollar of pipeline should be traceable. You build the infrastructure that makes that possible
• Build and maintain analytics and attribution pipelines (GA4, GTM, CRM integrations, event tracking)
• Connect the dots across tools: HubSpot, Intercom, Slack, Google Calendar, Supabase, and custom APIs
• Create reporting dashboards and automated alerts that surface what matters to Sales and Marketing leadership
• Design lead scoring and qualification models that improve with every cycle
• AI is not a buzzword here. You ship real LLM-powered workflows that save hours and improve outcomes
• Build AI agents and automations using Claude Code, LLM APIs, and orchestration frameworks
• Create prompt pipelines, evaluation frameworks, and feedback loops for AI-assisted workflows
• Automate repetitive GTM tasks: lead research, call prep, CRM hygiene, content personalization, outbound sequencing
• Identify high-leverage automation opportunities across the GTM stack and ship them
• The best GTM engineers don't just build for internal teams. They deploy solutions that shorten time-to-value for customers
• Build customer-embedded tools, onboarding automations, and integration workflows that drive activation
• Work directly with enterprise accounts to prototype custom solutions that unlock expansion revenue
• Create templates, starter kits, and self-serve tooling that reduce implementation friction
• Translate customer feedback into product insights and internal tooling improvements
• After 6-12 months:
• You've built and shipped 5+ internal tools or automations that the GTM team uses daily, and they measurably impact pipeline or efficiency
• Attribution and analytics pipelines are production-grade: leadership has real-time visibility into what's driving revenue
• AI-powered workflows are saving the team 10+ hours per week on previously manual tasks
• You've deployed at least one customer-embedded solution that accelerated activation or expansion for an enterprise account
• The GTM stack feels like an integrated system, not a collection of disconnected tools
• You've established patterns and frameworks that make it easy to ship the next automation in days, not weeks