Head Of GTM Engineering (AI Systems) - Remote Eligible

Head Of Engineering, Gtm Systems

At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms across industries such as SaaS, MarTech, FinTech, and EdTech.

Unlike an outsourcing agency, we place you directly with a client where you're hired in-house as a valued member of their team. This means you work closely with internal teams, contribute to meaningful projects, and have real opportunities for career growth.

Our client is an AI-first GTM (Go-To-Market) systems company founded by experienced revenue leaders. They build end-to-end automated revenue engines that transform market signals into qualified pipeline using AI agents, workflow automation, and scalable data infrastructure.

Their stack combines tools like workflow automation platforms, enrichment systems, CRM integrations, and custom AI agent orchestration layers—serving high-growth companies scaling from $1M to $100M+ ARR.

We're hiring a Head of Engineering, GTM Systems to lead the transition from no-code automation to Claude Code-powered AI agent architecture.

This role is for a hands-on builder who has deep experience in Clay-based GTM systems and is now building scalable, production-grade systems using Claude Code and modern programming languages.

You will own the infrastructure that powers revenue generation—designing intelligent systems that scale across clients and evolve with real-time signals.

Key Responsibilities

AI Agent Architecture & Engineering

• Design and build AI-powered GTM systems—from signal detection and enrichment to campaign orchestration and response handling
• Develop scalable backend systems using Python, JavaScript, or TypeScript
• Architect integrations across CRMs, APIs, data sources, and outreach platforms
• Build reusable agent frameworks, templates, and SDK-like components for rapid deployment

Team Leadership & Engineering Culture

• Lead and scale a distributed team of engineers (including offshore talent)
• Establish best practices for version control, testing, documentation, and deployment
• Mentor automation-focused engineers into AI-agent and software engineering roles
• Own hiring, onboarding, and performance management

Platform Development & Innovation

• Drive the shift from no-code workflows to code-first AI systems
• Evaluate emerging AI tools, LLM capabilities, and automation frameworks
• Contribute to internal AI tooling and reusable automation libraries
• Prototype and validate new automation opportunities quickly

Systems Reliability & Performance

• Ensure system reliability through monitoring, logging, and error handling
• Optimize infrastructure for cost, performance, and scalability
• Build observability systems to proactively detect and resolve issues