AI Product Engineer

AI Product Engineer

Full-Time 90000 - 110000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Build cutting-edge AI features and workflows for Fortune 500 procurement teams.
  • Company: Join Magentic, a forward-thinking tech company backed by top investors.
  • Benefits: Competitive salary, equity, enhanced parental leave, and 25 days holiday.
  • Other info: Dynamic team with backgrounds from OpenAI, Meta, and NASA, plus great career growth.
  • Why this job: Make a real impact in AI while shaping the future of global supply chains.
  • Qualifications: Experience in engineering and shipping LLM-based solutions, with strong Python skills.

The predicted salary is between 90000 - 110000 £ per year.

The Role

We're looking for an AI Engineer to build the agentic core of our product. You'll work closely with our CTO and own LLM-based features and agentic workflows end to end, from the agent framework through to the tooling that connects it to a customer's ERP. You’ll ship the cutting edge models and paradigms to Fortune 500 procurement teams. Procurement is a demanding domain for agents: long-running workflows over messy data, where a wrong answer costs a customer real money. You'll decide how multi-agent collaboration works here, and how we benchmark it for performance, safety and behaviour. We're building next-generation agentic systems that can manage entire procurement workflows, with a mission to make global manufacturing supply chains more resilient to an ever-changing world. That's a $3tn market opportunity. We're backed by world-class investors including Sequoia Capital, and you'll be joining a team bringing together experience from OpenAI, Meta, Revolut, NASA and McKinsey.

What You’ll Do

  • Own development and deployment of LLM-based features and agentic workflows end-to-end
  • Develop new agentic frameworks to handle multi-agent collaboration.
  • Benchmark LLMs across performance, safety and behavioural monitoring.
  • Operationalise AI features by building tools to connect them to customer systems
  • Collaborate with customers and internal teams to understand customer problems and design optimal solutions

You Might Be a Great Fit if You

  • Have engineering experience at tech and product-driven companies, so you know what great code looks like
  • Have experience shipping LLM-based solutions to production
  • Have a deep understanding of the core technology behind language models, as well as computer science fundamentals
  • Have built features end-to-end in Python
  • Enjoy communicating with both technical and non-technical stakeholders.

Compensation and Benefits

At Magentic, we recognise and reward the talent that drives our success. We offer:

  • Competitive Equity: play a real part in Magentic’s upside
  • A salary of £90,000 - £110,000 per annum
  • Enhanced parental leave
  • 25 days holiday exc bank holidays, plus an extra day for our Christmas shutdown
  • In-office lunches provided
  • Salary sacrifice pension and nursery schemes
  • Hybrid London HQ (3 days per week, with flex if you have appointments etc)
  • Annual team retreat—a fully-funded off-site to recharge, bond, and build

Our Interview Process

We can move quickly through these stages, so let us know if you have any timelines we need to meet.

  • Initial call (30 mins): this first step is an opportunity for you to hear more about Magentic and the role, and for us to learn more about how your experience aligns with the role.
  • Skills interview (45 mins): in this step, we'll ask you to prepare a presentation and take Q&A.
  • In-person interview (half-day, paid): for the final step, we invite you to come meet the team in-person. We find this is the best way for candidates to get a sense of what working at Magentic is like. This day will include a culture interview, founder interview and a presentation task / discussion with the team.

Equal Opportunities and Accommodations Statement

At Magentic, our mission is to build AI that helps solve some of the world's most complex real world problems. We believe building a diverse workforce will be the key to solving this for our customers. Magentic is committed to creating a truly inclusive team and we’re proud to be an equal-opportunity employer. As we grow, we're intentional about building teams with a broad range of backgrounds, experiences and viewpoints, recognising that this leads to better ideas, stronger collaboration and better outcomes for our customers therefore we strongly encourage applications from all backgrounds and cultures to apply. We recognise that some groups remain underrepresented within the industry and are committed to creating an environment that celebrates and supports everyone. Everyone works differently, and we want to ensure our interview process gives you the best chance to show us what you can do. If you require any reasonable adjustments or accommodations, please let us know and we'll work with you to make the process accessible.

Responsible AI Statement

At Magentic, we are committed to developing artificial intelligence that benefits humanity. We push the limits of AI's capabilities and are dedicated to its responsible and safe deployment. Recognising the profound impact of AI, we ensure that its development is centred around human needs and safety, incorporating a wide array of perspectives to fulfil our mission.

AI Product Engineer employer: Magentic

At Magentic, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to take ownership of their projects and drive innovation in AI-driven enterprise solutions. With competitive compensation, equity opportunities, and a strong emphasis on professional growth, our London HQ offers a collaborative environment where you can thrive alongside a talented team from leading tech backgrounds. Join us in redefining the future of enterprise software while enjoying unique benefits like company-provided meals, a monthly social budget, and an annual team retreat to strengthen bonds and recharge.

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Contact Details:

Magentic Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Product Engineer

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Magentic or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Magentic.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Magentic.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Magentic that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace AI Product Engineer

LLM-based Solutions
Agentic Workflows
Multi-Agent Collaboration
Performance Benchmarking
Safety Monitoring
Behavioural Monitoring
Python Programming

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 Magentic.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Magentic 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 Magentic

✨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 Magentic 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.