AI & GTM Engineer

Responsibilities

• Audit existing marketing workflows across content, social, PR, growth, and design, and systematically redesign them with AI tooling to increase speed, quality, and scale.
• Build and maintain AI-powered content and campaign pipelines for internal teams and client accounts, reducing manual effort without sacrificing brand quality.
• Develop and own a firm-wide prompt library, AI SOPs, and workflow playbooks - the operational backbone that makes AI adoption stick across a 90-person global team.
• Identify, evaluate, and onboard new AI tools relevant to marketing and GTM; maintain and evolve the firm’s AI tooling stack as the landscape shifts.
• Partner with client teams to diagnose GTM bottlenecks and design AI-assisted solutions - from content at scale to campaign automation to research synthesis.
• Build no-code and low-code automations that connect AI tools into existing martech stacks (HubSpot, Notion, Slack, social platforms) using tools like Make, Zapier, or n8n.
• Train and upskill marketing teams across the firm on AI tools and workflows, raising the baseline AI fluency of every team you work with.
• Define and track the metrics that prove AI workflow impact - time saved, output volume, quality scores, and client adoption, and report findings to leadership.

Requirements - Core Technical Skills

• Expert-level prompt engineering across major LLMs (Claude, ChatGPT, Gemini, Perplexity) - you write system prompts, build multi-turn workflows, and iterate until the output is ready to ship externally.
• Hands-on experience with AI creative tools: image generation (Midjourney, Adobe Firefly), video (Runway, Sora, Kling), and audio (ElevenLabs) in a real marketing context.
• Workflow automation using no-code/low-code platforms (Make, Zapier, n8n) - you’ve connected APIs, built multi-step automations, and maintained them in production.
• Comfortable working with APIs, webhooks, and JSON - enough to connect AI tools even when there’s no native integration.
• Familiarity with AI-native martech: HubSpot AI, Jasper, Copy.ai, Notion AI, Sprout Social, and the broader martech stack these tools plug into.
• Experience building prompt templates, internal AI playbooks, and training materials that actually get used - not just written.

Analytical & Data Science Expertise

• Ability to use AI tools to synthesize research, competitive intelligence, and market data at speed, NotebookLM, Perplexity, and similar tools are already part of your workflow.
• Comfort measuring the performance of AI-assisted campaigns and workflows: you know how to A/B test AI-generated content and interpret what the data is telling you.
• Ability to translate AI workflow data and campaign performance into clear strategic recommendations for clients and internal stakeholders.
• Familiarity with analytics tools (GA4, HubSpot analytics, basic SQL a plus), you’re not a data scientist, but you’re not afraid of a spreadsheet or a dashboard.
• Strong critical thinking around AI outputs - you know when to trust the model and when to override it, and you build that judgment into the workflows you create.

Blockchain & Web3 Experience

• Familiarity with the web3 GTM landscape: how protocols, DAOs, and crypto projects build audiences, launch products, and grow communities is not foreign to you.
• Working knowledge of how AI and blockchain intersect: AI agents, on-chain AI applications, decentralized compute, and what these mean for how clients go to market.
• Awareness of on-chain analytics tools (Dune, Nansen, Arkham, Flipside) and how data from these platforms can inform GTM strategy and content.
• Strong interest in the space is the baseline: prior experience in crypto or web3 marketing environments is a strong plus.

This position is ideal for someone who…

• Doesn’t care about rigid job titles: is equally comfortable acting as a strategist, a builder, a trainer, or an operator depending on what the problem demands.
• Loves tinkering and experimenting with new tools before anyone else has heard of them: and has the judgment to know which ones are worth deploying at scale.
• Gets energy from hard, ambiguous problems: not from following established playbooks, but from writing the new ones.
• Ships fast and isn’t precious about being wrong on the first try.
• Wants to see their work create real client impact: not just live in a deck or a Notion doc that nobody reads.
• Believes AI is a multiplier, not a shortcut: and builds workflows that reflect the difference.
• Thrives in a fast-moving, globally distributed team where autonomy is high and there’s no one to hand the problem off to.