Marketing Engineer, Demand Generation

Product Genius•Boston, MA

4d•$150,000 - $190,000

About The Position

Product Genius is pioneering Large Interaction Models — bringing the power of generative AI to applications requiring real-time response on limited training sets. In eCommerce, we create "thinking websites" that personalize the shopping journey in real time, driving documented revenue lifts of 30%+. Engineering is our DNA. We apply that same rigor to our go-to-market systems. We believe data matters, experimentation matters, proof matters, and authentic customer value creates durable businesses. As our Marketing Engineer, you will own the architecture and execution of our AI-native demand generation engine — working directly with leadership and engineering to design a continuously learning awareness-to-trial pipeline powered by AI agents, workflow automation, experimentation systems, enrichment pipelines, and GTM infrastructure. This is a foundational role with enormous ownership and leverage.

Requirements

Systems thinking — you reason in workflows, feedback loops, and compounding advantages
Technical fluency with APIs and coding (ex Python), workflow automation, AI tooling, CRM architecture, and modern GTM infrastructure (Clay, Apollo, HubSpot, or similar strongly preferred)
Experience working with major Ads / Social platforms (Google, Facebook, LinkedIn, Reddit, etc)
Comfort vibe-coding lightweight workflows and scripts in Python or JavaScript
Deep analytical rigor — you build systems that generate insight, not just dashboards
Experimentation mindset — you form hypotheses quickly, test rigorously, and update based on evidence
AI fluency — you already use AI heavily and constantly look for leverage
3+ years in B2B demand generation, growth engineering, RevOps. Product-led growth experience preferred.
No specific degree required. Demonstrated ability to build systems, drive growth, and learn quickly matters more.

Responsibilities

Architect the growth system — Design end-to-end growth infrastructure integrating referral, paid, outbound, social, CRM, and product signals into a cohesive, continuously improving system.
Build AI-assisted workflows — Automate lead enrichment, segmentation, outbound sequencing, content generation, performance analysis, and workflow orchestration using tools like Clay, Apollo, and custom automations.
Manage an AI agent workforce — Design agents that handle data acquisition, enrichment, content transformation, research, and campaign execution.
Drive demand generation — Own performance across paid and outbound channels (Google, Meta, LinkedIn, email, partnerships). Build high-intent pipeline and drive awareness-to-trial conversion.
Treat growth like a product — Instrument the full funnel. Measure CAC, conversion, and pipeline quality. Use experimentation to isolate variables and improve system performance.
Build feedback loops — Connect prospect/customer behavior, campaign performance, CRM activity, and revenue outcomes into actionable intelligence using an AI-first systems approach.
Collaborate with sales — Optimize lead scoring, prioritization, handoff systems, and sales enablement workflows.
Engineer content systems — Transform organizational knowledge, CRM data, and sales conversations into high-performing ads, outbound messaging, landing pages, and email sequences.