GTM Engineer

Requirements

• 2-5 years of experience writing production code in TypeScript/Node.js, Python, or similar.
• 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) Experience in a forward-deployed engineering, solutions engineering, or GTM engineering role at a high-growth startup.
• (Desirable) Familiarity with enterprise SaaS sales cycles and customer-embedded delivery.
• (Desirable) Experience with data visualization and reporting tools (Plotly, Recharts, custom dashboards).
• (Desirable) Background in market research, consumer insights, or B2B SaaS.
• (Desirable) Open-source contributions or a portfolio of shipped side projects.

What the job involves

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.