Marketing AI Operations Engineer

Job Advert

We’re a high-performance brand, growing fast, and we take how we work as seriously as what we sell. This is a new role in a new team building the systems that will shape how modern marketing operates here. That means designing and deploying agents, workflows, and automation layers that sit underneath how campaigns are planned, produced, tested, and improved.

We’re not looking for someone to simply “use tools” or stitch together prompts. We’re looking for someone who builds operational systems: agents that execute repeatable marketing tasks, workflows that connect our tools and data, and feedback loops that continuously improve output quality and speed over time.

Your work will turn fragmented marketing processes into a coherent, scalable system that the team can rely on every day. This role sits at the intersection of marketing, automation, and applied AI systems design.

As our Marketing AI Operations Engineer, you'll turn a pipeline of automation ideas into live, adopted systems that make the team faster, leaner, and more commercially effective. You'll own the full journey: scoping the problem, building the workflow, embedding it with the team, and measuring the impact. Success in this role is defined by how effectively teams adopt and use the systems and agents you build, not just by what you personally deploy.

You’ll work across paid media, CRM, content, and creative production to identify where human effort can be reduced, where decision-making can be structured, and where agents can reliably take on execution or coordination work. The goal is not novelty - it’s leverage: making the entire marketing function faster, more consistent, and more scalable without increasing headcount at the same rate. If you want to build from scratch, define how a modern marketing team uses agent-

based systems in practice, and see your work directly influence live campaigns and commercial outcomes every day, read on.

What You'll Own

• Build real things: Design, build, and maintain AI-powered workflows across paid media, content, CRM, and creative using n8n, Make, or Zapier; connect APIs and LLMs to real marketing use case.
• Build team-facing systems: Design and deploy marketing agents and automated workflows that plug directly into how the team plans, produces, and iterates campaigns.
• Own the prompt layer: Engineer and maintain prompts across ad copy, email sequences, product content, and UGC frameworks; the quality bar is yours to set and defend
• Integrate the stack: Connect AI tooling into our existing martech so information flows cleanly and automatically where it needs to
• Build feedback loop infrastructure: Design and maintain the mechanisms that capture how AI outputs perform in the real world, from creative engagement to email conversion, and feed those signals back into prompts, workflows, and model inputs to drive continuous improvement
• Own bias and compliance controls: Establish and maintain guardrails that ensure AI-generated outputs are accurate, fair, and compliant with advertising standards and data privacy requirements; this includes regular audits of outputs, clear escalation paths, and documented controls the wider team can follow
• Make it stick: Create documentation, run short walkthroughs, and support go-lives so the team actually adopts what you build; a workflow nobody uses doesn't count
• Measure what matters: Track time saved, creative output velocity, error reduction, and adoption rates; iterate until the numbers move
• Stay sharp: Scout new AI and automation capabilities, prototype safely, and share what's genuinely useful; not everything that's new is worth building
• Do it properly: Follow best practices for data security, privacy, and responsible AI usage; keep your builds clean, documented, and maintainable

What Success Looks Like

• AI workflows are live, adopted, and measurably compressing time-to-publish for creative and copy
• Marketing teams are actively using the agents and workflows you’ve built as part of their normal workflow, without relying on you to operate them.
• Paid creative testing velocity increases without proportional growth in headcount or agency spend
• Brand consistency holds at scale; outputs don't read like they came from a machine
• Feedback loops are in place and actively improving output quality over time, so the system gets smarter, not just faster
• Bias and compliance controls are documented, audited, and trusted by the wider team
• The marketing team can brief, produce, and iterate faster because of systems you built and embedded including agent-driven workflows that reduce dependency on manual execution.
• You're identifying new AI capabilities and prototyping them before the business has to ask

Skills & Experience

Must-Have

• Proven experience building and operationalising AI or automation workflows; not just using tools, but systematising them end-to-end
• Strong hands-on prompt engineering across LLMs (GPT-4, Claude, Gemini) with production-grade outputs you can point to
• Practical experience with n8n, Make, or Zapier connected to real marketing or ecommerce workflows
• Experience designing feedback mechanisms that close the loop between AI output and real-world performance; not just building the pipeline, but improving it over time
• Working knowledge of bias risk in AI-generated content and how to build controls that catch problems before they go live, including awareness of UK/EU advertising standards and data privacy obligations (GDPR)
• Comfortable working across paid, email, content, and creative; you understand how the full funnel fits together
• Able to translate a messy marketing brief into a structured, working automation without hand-holding
• High written communication bar; you'll QA AI outputs, so your own standard needs to be above what you're checking

Nice-to-Have

• Light scripting ability (JavaScript or Python) for custom logic and API integrations
• Experience in a DTC, health, or nutrition brand environment
• Familiarity with paid media platforms and how AI tooling integrates with creative testing workflows
• Experience with analytics tooling: GA4, Klaviyo, Meta Ads Manager

Core competencies

• LLMs: ChatGPT (GPT-4), Claude, Gemini
• Automation: n8n, Make (Integromat), Zapier
• Creative & content: Midjourney, ElevenLabs, Runway, or equivalents
• CRM / Email: Klaviyo, Iterable
• Analytics & Ads: GA4, Meta Ads Manager, Google Ads, Datastudio
• Project management: Jira, or similar

Core traits

• Systems and agents thinker: you design for delegation to systems and agents, not personal execution. Your default question is “can this run without me
• Builder, not recommender: you build and deploy things, not slides about things
• Commercially grounded: every workflow connects back to speed, cost, or revenue
• High standards: output quality matters as much as output volume; you catch problems before they deploy
• Autonomous: you identify problems and solve them before they get escalated
• Curious, not distracted: you stay current on AI, but you know the difference between signal and noise

Core behaviours

• Pace: Know that speed is your greatest ally. It builds momentum and is key for growth. Go fast.
• Communication: Know that team is your greatest asset. Talk to them face to face, Don’t try to go alone.
• Trust: When you say you’ll do it, do it. When someone asks for help, you give it.
• Transparency: Nothing is off limits, to anyone at any time. Remove walls & call out red tape.
• Challenge: Get comfortable with feeling uncomfortable. We need you to go where you’re scared to.
• Learn: Drive a culture of experimentation and continuous improvement.
• 360 Management: Manage up, down and across. Regardless of title, everyone is a leader. So Lead.