GTM Engineering - Growth Marketing

Job Description

So, what will your new role look like?

Workleap’s Growth Go-To-Market (GTM) squad wants every important signal, product usage, web intent, ad spend, and creative performance to flow into a single revenue engine. You’ll design and ship the AI-powered systems, dashboards, and playbooks that turn those signals into pipeline, faster learning cycles, and happier sellers. Think “embedded engineer inside Marketing & RevOps” rather than back-office ops.

Responsibilities:

• Reusable automation modules – build backbone workflows (e.g., Clay, HeyReach, HubSpot, Snowflake, CommonRoom, SmartLead) that power dozens of outbound or nurture plays.
• GTM playbooks & enablement – translate every module into crisp SOPs, Loom demos, and copy-ready plays for AI agents, SDRs, marketers, or CSMs.
• Insight products – ship dashboards that surface ad ROAS, content engagement, and next-best-action suggestions.
• AI agents & content generators – deploy LLM tooling for rapid research, message personalization, and creative testing at scale.
• Data quality & deliverability – keep sender reputation ≥ 95 %, scores clean, and attribution airtight.

What does your future team looks like?

The GTM Engineering team is a lean, AI-native group within Marketing’s function. It includes a Senior Manager (GTM AI Engineering) and a GTM Architect, and partners daily with Sales, Demand Gen, Brand, and Data to build intelligent systems that eliminate manual work and accelerate execution. We’re not a support function- we’re builders. If you're excited by AI's power to design smart workflows, automate decisions, and amplify human creativity across Sales and Marketing, you'll find both challenge and purpose here.

Qualifications

• Growth-automation & full-stack engineering: shipping end-to-end features in Cursor/Python/TypeScript (Next.js), wiring REST & webhook APIs, and leaning on low-code orchestrators (n8n, Zapier) when it’s faster;
• Generative-AI workflow design: expert in prompt engineering, LLM chaining/agent orchestration, and vector search; able to spin up reusable AI components in hours;
• Funnel & performance analytics: fluent in SQL, cohort and conversion analysis, experimentation metrics, and dashboarding from warehouse to BI;
• RevOps systems & deliverability: models CRM objects, sequencing and lead-routing logic, plus the sender-reputation and compliance safeguards that keep campaigns humming.

Nice-to-have:

• PLG SaaS growth chops – you’ve operated inside a product-led funnel and know activation & expansion mechanics;
• Shipped an AI agent – built and deployed an LLM-powered agent that solved a real business workflow;
• Automated repetitive tasks with AI – turned a manual GTM or ops pain point into a fully hands-off process;
• Built features with an AI SDK – hands-on with OpenAI, Vercel AI SDK, or similar frameworks for rapid prototyping;
• Taught the community – published blog posts, Looms, or conference talks that explain technical concepts in plain language.