AI Engineer Marketing Tools

You've already done this before - you've walked into a company, spotted where AI could solve a real marketing problem, and built the solution yourself, end to end. You're not looking for your first shot at this.

• Strong, proven experience working with LLMs in production - prompting, fine-tuning, RAG, or agent-based systems

• Deep knowledge of agent frameworks and how to design multi-step, tool-using workflows

• Proven experience building AI tools or automations specifically for Marketing - reporting automation, creative generation, campaign optimization, attribution modeling, or similar

• Solid understanding of how a digital marketing department operates: user acquisition, growth channels, performance marketing, SEO, ASO, ASA, and attribution

• Strong Python skills and comfort integrating APIs, webhooks, and third-party tools (ad platforms, analytics, MMPs)

• Business vision - you understand how a marketing team operates and can spot high-leverage opportunities for automation without being told where to look

• Comfortable working in fast-moving, data-heavy environments where speed and iteration matter

• Ability to work autonomously, prioritize based on impact, and ship without waiting for perfect conditions

• Experience with agent frameworks (LangChain, LlamaIndex, CrewAI, or similar)

• Experience with automation/workflow platforms (n8n, Zapier, Make)

• Experience building tools involving data pipelines, dashboards, or reporting systems

• Prior experience in a startup or fast-moving, resource-constrained environment

Labhouse is a Barcelona-based startup studio building AI-powered mobile apps used by hundreds of thousands of people worldwide. Our products - including Invoice Fly and Summary AI - are designed to make everyday tasks faster, smarter, and simpler through a subscription model that puts the user first.

We were founded by Andrés Bou and Horacio Martos, the duo behind SocialPoint (acquired by Take-Two Interactive), and we operate with the mindset of a product company: small teams, high ownership, and a relentless focus on building things that matter.

Would you like to make an impact as part of a company that builds the best mobile apps used by millions of users worldwide? If so, discover your next challenge below.

At Labhouse, AI isn't just what we ship to users - it's how we operate internally. As our AI Engineer, Marketing, you'll design and build LLM-powered tools, agents, and automations specifically for our Marketing and Growth team - turning manual, repetitive, or slow marketing processes into fast, scalable systems.

This is a hands-on, high-ownership role sitting at the intersection of AI engineering and marketing. You will:

• Identify manual, repetitive, or slow processes within Marketing and turn them into AI-powered tools and automations

• Design and build LLM-based agents that can reason, use tools, and complete multi-step marketing tasks autonomously (reporting, creative generation, campaign analysis, channel optimization)

• Own projects end-to-end - from scoping the problem with the marketing team, to designing, building, and shipping the solution

• Integrate LLMs and agents with marketing platforms and data sources (ad platforms, attribution tools, analytics, dashboards)

• Work directly with Growth, Performance Marketing, and ASO/SEO leads to understand where AI can unlock the most impact - and translate that into working products

• Measure the productivity and performance gains your work generates, and iterate based on real usage

We care more about what you've built than where you studied. A degree in Computer Science, Engineering, or a related technical field is a plus, but relevant hands-on experience matters more than the diploma.

You live and breathe AI tools - not just LLM APIs, but the broader ecosystem of agents, copilots, and automation platforms. You stay on top of the state of the art and know how to turn new capabilities into practical, working tools fast.

You communicate clearly with both technical and non-technical stakeholders. You know how to interview a team about their pain points, translate that into a technical solution, and explain the result in terms they care about.