At a Glance
- Tasks: Design and build AI evaluation and observability systems that make a real impact.
- Company: Join CreateFuture, an AI-native consulting partner with a people-first approach.
- Benefits: Enjoy 35 days leave, private medical insurance, and a 5% pension match.
- Other info: Work in a dynamic environment with opportunities for hybrid and remote work.
- Why this job: Be part of a supportive culture that values your growth and flexibility.
- Qualifications: Strong Python skills and hands-on AI engineering experience required.
The predicted salary is between 63000 - 77000 £ per year.
Working at Create Future Create Future is an AI-native consulting partner where people do work that matters and are supported to do it well.
We work alongside organisations such as Pay Pal, adidas, Nat West, Fan Duel and Money Saving Expert, building digital products and services that make a difference while always putting people first.
We’re a team of creators.
We write code, shape delivery, build go-to-market strategies, develop AI solutions and create the practices that support our people.
We work side by side with our clients, challenging what’s not working and helping them to build the future.
Our commitment to craft, quality, and culture has helped us scale to over 600 people in just a few years.
- Our UK Benefits
- 35 days leave (including bank holidays).
- Private medical insurance.
- Enhanced parental and adoption leave.
- Financial coaching + 5% pension match.
- 40 hours of paid learning and development.
- View our full list of UK benefits.
Create Future is a Great Place to Work-Certified™ company and has won Best Workplaces UK multiple years in a row. Join us on our journey. Let’s create tomorrow, together, today.
About the role and team
You’ll join our AI Engineering team with a focus on evaluation, experimentation, and observability — building the systems that tell us whether our AI features actually work, and keep working, in production.
This is a hands-on, technical role representing Create Future day to day, working across eval platforms, golden datasets, and production monitoring for AI-native systems.
What you’ll be doing
- Design and build eval and observability pipelines using platforms such as Braintrust, Lang Smith, Arize, or Weights & Biases.
- Curate golden datasets and design LLM-as-judge and human-in-the-loop scoring pipelines.
- Build production observability for AI features: token-level tracing, quality signal monitoring, hallucination and refusal detection, and cost attribution per use case.
- Wire eval gates into CI/CD promotion paths so quality checks are enforced before release, not just measured after.
- Turn eval and observability data into decisions that engineering and product teams will actually act on.
- Work with engineering and product to interpret scores and know when a result is telling us something real versus noise.
We’d love to talk to you if you
- Have strong Python skills and hands-on AI engineering experience, particularly around evals and observability.
- Have used Braintrust, Lang Smith, Arize, Weights & Biases, or a similar platform in production.
- Are comfortable designing scoring pipelines and know how to sanity-check whether a score means anything.
- Have enough CI/CD fluency to wire eval gates into a promotion pipeline.
- Can communicate what the data means clearly enough that engineering and product teams act on it.
What we’ll offer you
We trust people to do their best work.
That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally.
You’ll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do.
We offer flexible working, including hybrid and remote options.
Our office hubs are located in Edinburgh, Leeds, Manchester, London and Bulgaria, with occasional travel to client sites or Create Future offices when needed.
We trust you to manage your time balancing collaboration with client time and focused work.
What matters is the impact you have, not how busy you look.
Our hiring process
We try to keep our hiring process clear, fair and respectful of your time.
We aim to get back to everyone who applies and we will be upfront about where you are in the process.
It usually looks like this: Call with our Talent Acquisition Team Role specific capability interview Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation.
We will explain what is involved before anything happens.
Inclusion at Create Future
We believe diverse teams build better workplaces and better products.
We want Create Future to be a place where people feel able to be themselves and do their best work.
If you need any adjustments or support during the application process, just.
We will do what we can to help.
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Senior AI Engineer in London employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer in London
✨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 Doist 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
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✨Tap into Online Developer Communities
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We think you need these skills to ace Senior AI Engineer 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 Doist.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Doist 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 Doist
✨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 Doist 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.
