[Hiring] GTM Engineer @Lorikeet

Role Description

We're looking for a GTM Engineer to own the systems that generate pipeline — someone who thinks like an engineer but executes like a marketer. You'll build AI-powered marketing infrastructure, run signal-based prospecting at scale, and drive growth loops across organic, paid, and lifecycle marketing.

This isn't a traditional demand gen role. You'll use Claude Code, Clay, and modern AI tooling to build things that would have required a team of five a few years ago. You'll own experimentation velocity, not just campaign execution.

You'll report to the Head of Marketing and work cross-functionally with sales, product, and forward-deployed engineering.

What you'll do

• Build AI-powered marketing infrastructure
• Design and operate AI agents that run marketing workflows autonomously — including lead enrichment, campaign personalisation, content production, and signal monitoring
• Build experimentation infrastructure that tests messaging, channels, and sequences faster than traditional marketing teams thought possible
• Create self-improving systems with evals, feedback loops, and guardrails that get better without constant supervision
• Run signal-based prospecting
• Build and optimise outbound engines using Clay, Apollo, RB2B, Unify, Instantly, and similar tools
• Surface buying signals (hiring, funding, competitor moves, contract renewals) and route them to sales with full context
• Design enrichment workflows that prioritise accounts automatically and identify warm intro paths
• Drive growth loops
• Own lifecycle marketing: nurture sequences, re-engagement campaigns, and credit consumption alerts that drive expansion
• Run 1:many ABM campaigns targeting industry marketing account lists
• Build and iterate on paid campaigns (LinkedIn, Google, Reddit) with rapid A/B testing
• Connect organic content (Steve's LinkedIn, SEO/GEO) to conversion infrastructure
• Own experimentation velocity
• Run 4–6 marketing experiments per month with clear hypotheses, metrics, and iteration cycles
• Document what works and systematise successful experiments into repeatable playbooks
• Track pipeline influence, reply rates, meetings booked, and cost per meeting across all channels

Qualifications

• 3–6 years in growth marketing, marketing ops, revenue ops, or a hybrid sales/marketing role at a B2B SaaS company
• Genuine fluency with AI tools — building with Claude Code, Cursor, or similar, not waiting for someone else to build for you
• Experience with the modern GTM stack: Clay, Apollo, HubSpot, Unify, or similar (or demonstrated ability to learn fast)
• Quantitative mindset: you think in funnels, conversion rates, cohort analysis, and attribution models
• Comfort with ambiguity: we're building the playbook, not executing an existing one
• Consulting or product background is a plus — as is experience in growth or as an SDR/BDR
• Strong communication skills: you'll work across sales, product, and marketing