engineering
Posted 3 days agoAI Marketing Engineer
at Legora
New York City, United StatesOn-site
Responsibilities
- - Build robust integrations: Connect AI agents directly into our marketing data stack to ensure seamless data flow and execution.
Requirements
- Our AI-native workspace lets legal professionals move faster, think more clearly, and operate with sharper precision.
- We’ve scaled to $100M+ in ARR, with teams across Europe, North America and APAC, and continue to expand through acquisitions including Qura, Walter AI and Graceview.
- The Role We're looking for an AI Marketing Engineer to join our marketing team in NY or SF.
- This role sits at the intersection of marketing craft and AI engineering, working hand-in-hand with leaders across brand, product marketing, revenue marketing, and marketing ops.
- Your job is to identify bottlenecks in our marketing machine and reimagine those workflows with AI agents.
- You understand how marketing teams think and what they care about, which means you can design AI systems that teams actually adopt and trust.
- You are energized by turning slow, manual, high-touch workflows into fast, reliable, low-touch systems and you know how to do it with frontier models.
- What You’ll Do - Reimagine Marketing Workflows with Agents: Partner with marketing leadership to design and deploy AI-native workflows with human-in-the-loop supervision.
- - Own the lifecycle from scoping to delivery: Solve one problem at a time, leading the full lifecycle of internal AI solutions from input collection, problem scoping, prompt engineering through to integration, testing, and iteration.
- - Act as an internal evangelist: Bring a point of view on rapidly evolving AI landscape helping the broader team understand what is real and what is hype.
- What You Bring - Marketing Ops and Automation Roots: A strong track record of building automations, AI workflows with skills and tool integrations. - Hands-on AI Tinkering:
- Experience with LLMs, prompt engineering, skills and agentic orchestration frameworks; you know how to manage context, structure model outputs and chain tasks together. - A Builder Mindset: you see a slow or broken process and your first thought is "I can fix that".