Founding Technical GTM (AI Infrastructure)

Key Responsibilities

• Data Enrichment & Waterfalls: Build automated multi-vendor data waterfall pipelines to pull, clean, deduplicate, and enrich raw lead and account data.

• CRM & Tool Integration: Connect CRMs (Salesforce, HubSpot), marketing automation platforms, and sales engagement tools via APIs, webhooks, and orchestration tools.

• Workflow Automation: Design event-driven workflows that handle lead scoring, dynamic routing, account sourcing, and multi-channel sequencing without manual spreadsheet copy-pasting.

• AI & Agent Implementation: Wire AI tools, LLMs, and Model Context Protocol (MCP) servers into the GTM stack for automated research, signal detection, and personalized outreach.

• System Maintenance & Hygiene: Monitor data completeness, prevent stale or duplicate records, and fix broken API or webhook triggers before they stall active deals.

Required Skills & Tech Stack

• Scripting & Querying: Basic to intermediate proficiency in SQL, Python, or JavaScript for custom API calls and data logic.

• Orchestration & Automation: Experience with visual or code-first workflow engines like n8n, Make, or Zapier.

• GTM & Data Platforms: Hands-on experience with modern outbound and data tools like Clay, Apollo.io, Salesforce, and HubSpot.

• AI & Prompt Engineering: Structuring reliable AI prompts, agentic workflows, and context pipelines that avoid hallucinations.

• Commercial Fluency: Understanding of Ideal Customer Profiles (ICPs), pipeline attribution, and B2B sales/marketing metrics.

Massive builds software and services for teams that need to manage complex operations at scale. We work with organizations across various industries to solve problems around coordination, data management, and workflow automation. Our team values thoughtful problem solving and direct communication. We're looking for people who are interested in understanding customer needs deeply and building tools that make a real difference in how teams work together.