At a Glance
- Tasks: Create AI-powered prototypes and solutions to enhance marketing productivity.
- Company: Join Amazon Ads Marketing's innovative AI-native team.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on creativity and problem-solving.
- Why this job: Be at the forefront of AI transformation in marketing and make a real impact.
- Qualifications: Experience in coding with Python/JavaScript and a passion for UX design.
The predicted salary is between 67500 - 82500 £ per year.
Amazon Ads Marketing is building an AI-native team to drive the transformation of the marketing organization to integrate AI into our operating model with precision and scale.
We are looking for AI Builders who are passionate about using AI-assisted development to build solutions that make marketers dramatically more productive.
As a design technologist on this team, you will operate at the intersection of AI-native development, UX design, and marketing operations.
You will build prototype solutions, working agents, and production-ready tools that solve marketer pain points.
Your work will directly drive the organization's productivity goals by shipping AI-relevant use cases from pilot to production.
This is a ground-floor opportunity to build a new team approaching the work through AI-native workflows.
You will work closely with marketing stakeholders, UX designers, product managers, and engineering partners to identify where AI can absorb labor-heavy work, then build the solutions that make it happen.
Your prototypes and reference code will set the standard for how AI transforms marketing at Amazon Ads.
You are an independent contributor.
You build prototypes and working samples that creatively solve difficult business and technology constraints.
Your scope is on medium-to-large projects where the product strategy is often defined, but the UX and technology approach is not.
You engage proactively with stakeholders to define priority use cases, logical workflows, and tech-forward solutions.
- Key job responsibilities
- Build AI-powered prototype solutions, agents, and automations that solve Ads Marketing pain points.
Produce working samples, agent frameworks, and reference code demonstrating how AI-powered marketing workflows can be implemented and scaled.
- Transform defined UX and marketing workflow ideas into working code using AI-assisted development tools and technologies (Python, Java Script, Node, AWS services, API integrations).
Prototype and ship AI use cases from pilot to production, directly contributing to productivity goals.
- Work backward from marketers and collaborate with product, design, and engineering teams to iterate on optimal experiences.
Identify UX and workflow issues before the dev/test cycle when fixes are less costly.
- Evaluate first-party and third-party AI tools and their integration with core marketing systems, ensuring solutions account for real-world constraints.
Develop reusable prototyping methods, agent frameworks, and reference architectures enabling rapid problem-solving.
- Contribute to creating and adopting prototyping tools, frameworks, and platforms for the team and broader marketing organization.
Document prototypes to preserve intent and learnings for future team members.
- Participate in design reviews, present work to stakeholders, and advocate for the marketer's perspective in all AI-powered solutions.
- A day in the life
This AI Builder prototypes AI-powered marketing solutions using AI-assisted development tools.
They collaborate with internal stakeholders (UX designers, product managers, engineers, marketing ops) and serve marketers within Amazon Ads Marketing as primary customers.
The role solves labor-intensive workflow problems by coding prototypes in Python/Java Script, designing AI agents, evaluating tools for marketing integration, and participating in design reviews.
They move use cases from concept to production while establishing reusable frameworks that enable AI adoption across the marketing organization.
About the team
The Ads Marketing AI Enablement is a new team within Marketing Effectiveness & Intelligence (ME&I), responsible for driving the successful transformation of the Ads Marketing org to an AI native operating model.
The team's primary measure of success is value-based productivity attributed to AI transformation.
AI Design Technologist, Marketing Productivity, Amazon Ads Marketing in London employer: Amazon Inc.
At Amazon Development Centre in Edinburgh, we are committed to fostering a collaborative and inclusive work culture that empowers our employees to innovate and excel. As an Applied Scientist in our Intelligent Talent Acquisition team, you will have the opportunity to work on cutting-edge machine learning technologies that directly impact recruitment processes, while benefiting from mentorship and professional growth opportunities. Join us to make a meaningful difference in how talent is acquired globally, all within a vibrant city known for its rich history and dynamic tech scene.
StudySmarter Expert Advice🤫
We think this is how you could land AI Design Technologist, Marketing Productivity, Amazon Ads Marketing in London
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace AI Design Technologist, Marketing Productivity, Amazon Ads Marketing in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Amazon Inc..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Amazon Inc. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Amazon Inc.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Amazon Inc. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
