At a Glance
- Tasks: Design and build AI-powered workflows, tackling complex real-world problems.
- Company: Fast-growing AI company transforming professional services with innovative solutions.
- Benefits: Competitive salary, hands-on experience, and opportunities for growth in a dynamic environment.
- Other info: Join a collaborative team and shape the future of AI in professional services.
- Why this job: Make a real impact by building serious AI systems that enhance decision-making.
- Qualifications: Experience in AI product development and strong coding skills required.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About MosaiQ
MosaiQ is a fast-growing AI company transforming how professional-services firms operate. We work with consulting teams, private equity funds, investment advisors, and other knowledge-driven organisations to turn their expertise, judgment, and workflows into AI-powered systems — deployed in days, not months. This is not “AI tooling for demos.” This is production AI embedded into real decision-making and revenue-critical workflows.
Our Uniqueness
- We reverse-engineer real work, not abstract use cases
- We map tacit knowledge and judgment, not just data
- We build hybrid AI + human systems that actually get used
- We augment experts rather than replace them
- We deploy custom AI directly into business processes, with measurable impact
- We work hands-on with decision-makers who value speed, quality, and judgment
The Role
We are looking for a Senior Full-Stack / AI Engineer to work closely with the founding team and the core team to design, build, and deploy real AI systems for demanding professional-services clients. You will not be handed toy problems or isolated tickets. You need to be a system thinker and ready to tackle complex problems. You will help turn messy, high-stakes workflows into robust AI-powered products, from architecture to deployment. Your work will directly shape MosaiQ’s platform, its AI modules, and how clients experience AI in practice.
Your Responsibilities
- AI Systems & Product Engineering
- Design and build AI-powered workflows end-to-end (backend, frontend, orchestration)
- Implement and iterate on AI modules (LLMs, agents, retrieval, evaluation loops)
- Translate real business processes into reliable, testable systems
- Balance speed, robustness, and long-term maintainability
- Build and evolve product interfaces used by real clients
- Develop APIs, services, and data pipelines supporting AI workflows
- Own features from concept → implementation → deployment
- Contribute to platform architecture and core components
- Design prompts, system instructions, and evaluation criteria
- Implement human-in-the-loop workflows where judgment matters
- Debug failure modes, hallucinations, and edge cases
- Improve reliability, consistency, and explainability of outputs
- Work directly with the founder on product direction and trade-offs
- Sit close to client problems to understand real constraints
- Help shape what becomes reusable platform capability vs. bespoke logic
- Document patterns, learnings, and internal building blocks
Who You Are
You’ll thrive here if you:
- Are a senior builder, comfortable owning systems end-to-end
- Enjoy understanding how businesses actually work, not just code in isolation
- Think in systems, workflows, and failure modes
- Are pragmatic: you care about what ships and what works
You already:
- Write production-grade code
- Use AI tools daily to accelerate your own work
- Understand trade-offs between speed, correctness, and scalability
Core skills
- Have built AI products beyond demos or notebooks
- Have experience with:
- LLM orchestration / agents
- RAG systems and knowledge layers
- Evaluation frameworks for AI outputs
- LangChain / LangGraph / similar
- Claude / OpenAI APIs in production
- Vector databases, embeddings, structured retrieval
Mindset That Matters
- Builder mentality — you ship, iterate, and improve
- Bias to action — progress today beats perfect next quarter
- Ownership — you take responsibility for outcomes, not just tasks
- Product thinking — you care how systems are used, not just how they’re built
What You Gain
- Direct exposure to real client problems and high-stakes use cases
- The chance to build serious AI systems, not slideware
- Deep experience turning expert workflows into AI-powered products
- A central role in shaping MosaiQ’s technical and product foundations
- The opportunity to grow into a core technical leader as the company scales
Artificial Intelligence Engineer in Bournemouth employer: MosaiQ Labs
Contact Detail:
MosaiQ Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Bournemouth
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those working at companies you admire. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects and contributions. This is your chance to demonstrate your ability to tackle complex problems and build real-world applications, which is exactly what MosaiQ is looking for.
✨Tip Number 3
Prepare for interviews by understanding the company’s unique approach. Dive deep into how MosaiQ transforms professional services with AI. Tailor your responses to highlight how your experience aligns with their mission of embedding AI into decision-making processes.
✨Tip Number 4
Don’t just apply anywhere—apply through our website! It shows you're genuinely interested in joining MosaiQ and gives you a better chance of being noticed. Plus, it’s a great way to stay updated on any new opportunities that pop up.
We think you need these skills to ace Artificial Intelligence Engineer in Bournemouth
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the role. Highlight your experience with AI systems and full-stack development, and show us how you can tackle complex problems just like we do at MosaiQ.
Showcase Your Projects: Include examples of AI products you've built or contributed to. We want to see your hands-on experience, so don’t hold back on sharing those impressive projects that demonstrate your skills in real-world applications.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your thought process and how you approach problem-solving. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join the MosaiQ team!
How to prepare for a job interview at MosaiQ Labs
✨Understand the Business Context
Before your interview, take some time to research how MosaiQ operates within the professional-services sector. Familiarise yourself with their approach to AI and how it integrates into real business processes. This will help you speak confidently about how your skills can directly contribute to their goals.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss specific examples of complex problems you've tackled in the past. Highlight your experience with AI systems and how you've turned messy workflows into efficient solutions. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Demonstrate Technical Proficiency
Make sure you can talk in-depth about the technologies and tools mentioned in the job description, like LLM orchestration and APIs. Bring along examples of your production-grade code or projects that showcase your ability to build AI products beyond demos. This will show that you’re not just familiar with the concepts but have practical experience.
✨Emphasise Collaboration and Product Thinking
MosaiQ values teamwork and understanding client needs. Be ready to discuss how you've collaborated with others in previous roles and how you approach product thinking. Share instances where you’ve worked closely with stakeholders to ensure that the final product meets real-world requirements.