Own the GTM analytics and AI-driven optimization across integration, audience signals, and hyper-personalized outreach to accelerate win rates and reduce cycle time.

• What you’ll Own 1) Though Leadership on GTM Analytics - Collaborate with the VP of Growth Marketing to inform and lead the thinking around tools, analysis, and approach for solving pressing go-to-market issues using AI in conjunction with conventional tools.
• Identify and prioritize the most pressing or promising opportunities to advance Menufy’s ability to take market share
• Develop AI workflows to pursue advanced analytics to inform decisions
• Develop AI workflows to orchestrate continually improving campaigns that give Menufy an outsized advantage in the market
• What you’ll Own 2) GTM Stack Integration & Automation - Own the technical integration layer between Menufy's website, Google Ads, Meta Ads, and HubSpot (marketing automation) zero-latency data flow between them is the baseline expectation.
• Salesforce is managed by the Sales Operations team; the GTM Engineer works with sales ops to specify, request, and validate the data handoffs that feed marketing campaigns and ad audiences.
• Partner with Sales Operations to design and validate automated pipelines that push lead-scoring signals from Salesforce into ad audiences in near real-time. The GTM Engineer owns the specification, the HubSpot-side logic, and the ad platform configuration; sales ops owns the Salesforce admin layer. The shared goal is eliminating manual export/import cycles that create 24–72-hour lag.
• Architect event tracking (website, landing pages, email clicks, ordering path drop-offs) so every campaign has closed-loop attribution from ad impression to signed contract.
• Reduce GTM stack fragmentation: identify redundant tools, consolidate where possible, and document the single source of truth for each KPI.

• What you’ll Own 3) AI-Powered ICP Discovery & Campaign Intelligence - Work with Sales Operations to access structured exports of Salesforce call records, CRM notes, and win/loss data, and work with the Engineering team to access customer performance and tool usage data to extract: (a) the sharpest Ideal Customer Profile signals, (b) the messages that correlate with closed-won, and (c) the friction points that correlate with churn or lost deals. Direct database access is not available; the GTM Engineer must be able to specify precisely what data they need and validate its completeness when received.
• Translate those signals into look-alike audiences pushed directly to Google and Meta — with a documented feedback loop so audiences refresh as new data arrives.
• Build 'self-healing' campaigns: automated rules that reallocate budget toward top-performing ad sets, pause underperformers, and surface anomalies (CPL spike, CTR drop) to the VP of Growth before they become material misses.
• Own A/B test architecture — hypothesis generation, audience splits, statistical significance thresholds, and results reporting — so the team runs 2-3x more experiments per quarter without adding headcount.

• What you’ll Own 4) Hyper-Personalized Restaurant Outreach - Develop an automated workflow that audits a prospect restaurant's digital footprint (Google Business Profile score, website structure, online ordering presence, review velocity) and compares it against Menufy's best-in-class restaurant benchmarks.
• Use that gap analysis to auto-generate hyper-personalized outreach messages — email subject lines, ad copy variants, and AI agent conversation starters — each tuned to that specific restaurant's most visible gap (e.g., no online ordering, weak review velocity, unoptimized Google Business Profile).
• Deploy AI agents that advance asynchronous conversations with prospects autonomously — from first touch through qualification to a yes — without human SDR involvement. The GTM Engineer owns the architecture, prompt logic, conversation branching, and fallback rules that keep these agents on-brand and legally compliant across email and SMS channels.
• Integrate personalization signals into HubSpot so AI-agent-initiated conversations are context-enriched from the first message — not generic blasts — and every interaction is logged for closed-loop attribution

• What you’ll Own 5) Revenue & Pipeline Analytics - Own the GTM analytics layer: pipeline velocity by segment, CAC by channel, LTV:CAC ratios by cohort, and marketing-influenced revenue attribution — built in a dashboard the President and VP of Growth can interrogate directly.
• Run scenario models when channel mix, pricing, or ICP assumptions shift — the kind of FP&A-adjacent analysis that turns a 'what if we doubled spend on Google' question into a 10-minute, data-backed answer.
• Flag variance without softening it: if a channel misses CPL targets by >15%, the report says so on day one, not end-of-month.