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- Tasks: Build innovative multimodal agents that interact with real games and solve complex problems.
- Company: Exciting early-stage startup focused on autonomous game testing.
- Benefits: Competitive salary up to ÂŁ130k, equity options, and hybrid work model.
- Other info: Founding level ownership with excellent growth potential.
- Why this job: Shape the future of game testing with cutting-edge AI technology.
- Qualifications: Experience in computer vision and building multimodal agents.
The predicted salary is between 104000 - 130000 ÂŁ per year.
Founding Applied AI Engineer – Agentic Systems (Games) – up to £130k + Equity – Hybrid London
Built agents that actually act in the real world, not just predict? Worked with multimodal models, images, video, vision, and turned them into systems that make decisions and recover when things go wrong? Enjoy solving messy, real problems where reliability matters more than demos? If that sounds like you, keep reading.
The challenge
This is an early stage startup building autonomous agents that test games the way real players do. Not scripted bots. Not brittle automation. Proper agents that observe gameplay, reason over images and video frames, and take actions across real devices. The goal is simple to say and hard to execute: make studios trust agents more than manual QA.
You’ll be building multimodal agents that operate inside live games, across mobile and desktop, handling inconsistent UIs, timing issues, network lag, and all the things that break naive automation. This is about getting agents out of notebooks and into production.
What you’ll be building
- Multimodal agents that reason over images and video, often across multiple frames, and decide what to do next
- Vision driven agents that interact with real games, tapping, swiping, clicking, navigating
- Systems that follow loops, observe, decide, act, recover, not fixed scripts
- Automation that runs reliably across devices, OS versions, screen sizes, and edge cases
- Production grade agent systems that people trust to run unsupervised
Think less “prompting” and more systems thinking.
Why this role is different
- Founding level ownership, you are shaping how the core agent system is built
- Real production constraints, not research theatre
- Agents operating in the wild, not controlled demos
- A product that lives or dies on reliability
If you like seeing your work break, fixing it, and making it stronger, you’ll enjoy this.
About you
You’re likely an Applied AI Engineer, Computer Vision Engineer, or similar, and you:
- Have built multimodal or vision based agents using images and video, not just text
- Background in Computer Vision (YOLO, ResNET, EfficientNET etc)
- Familiar with Vision Agent and VLMs (LLaVA, CLIP, Flamingo etc)
- Have worked in similarly messy technical environments, automation, robotics, device control, autonomy, AV, or complex UI driven systems
- Comfortable working with QA’s and Testing Leads to understand their workflows
- Worked in an AI product start-up environment (ideally 0-1)
If you’ve built agents that actually do things and want to take real ownership, get in touch.
Email - mo@mbnsolutions.com
Call - 020 3773 6498
You must be eligible to work in the UK.
Computer Vision Engineer in City of London employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer Vision Engineer in City of London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the game. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects, especially those involving multimodal agents or computer vision. Share it on platforms like GitHub or your personal website. This way, potential employers can see your work in action, not just read about it.
✨Tip Number 3
Prepare for interviews by practising common questions related to AI and computer vision. But don’t stop there! Be ready to discuss how you’ve tackled real-world problems and what you learned from them. We want to hear about your thought process and how you approach challenges.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and take the initiative. Don’t hesitate to follow up after applying; it shows your enthusiasm and commitment!
We think you need these skills to ace Computer Vision Engineer in City of London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and computer vision shine through. We want to see that you’re not just ticking boxes but genuinely excited about building agents that can tackle real-world challenges.
Highlight Relevant Experience: Make sure to showcase any experience you've had with multimodal models or vision-based agents. We’re looking for specific examples of how you've tackled messy technical environments, so don’t hold back on the details!
Tailor Your Application: Don’t send a generic application! Tailor your CV and cover letter to reflect the skills and experiences mentioned in our job description. This shows us that you’ve done your homework and are serious about joining our team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensures you get all the latest updates from us. Plus, it makes the process smoother for everyone!
How to prepare for a job interview at MBN Solutions
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like YOLO, ResNET, and multimodal models. Brush up on your knowledge of vision-driven agents and be ready to discuss how you've applied these in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare examples of messy technical challenges you've faced and how you tackled them. This role is all about reliability and real-world applications, so highlight your experience in building systems that can recover from failures.
✨Understand the Company’s Vision
Research Agentic Systems and their approach to game testing. Be ready to discuss how you can contribute to their goal of making studios trust autonomous agents over manual QA. Showing genuine interest in their mission will set you apart.
✨Practice Systems Thinking
Since the role emphasises systems thinking over simple prompting, prepare to discuss how you approach building complex systems. Think about how you would design an agent that interacts with real games and be ready to share your thought process during the interview.