At a Glance
- Tasks: Lead the design and deployment of innovative AI applications.
- Company: Join a pioneering firm transforming businesses with Generative AI solutions.
- Benefits: Enjoy flexible working and a competitive salary of £70,000-£100,000 plus benefits.
- Other info: Engage with senior stakeholders and drive innovation across multiple projects.
- Why this job: Be at the forefront of AI technology, shaping strategies and mentoring future engineers.
- Qualifications: 5+ years in software development with expertise in scalable AI solutions and LLMs.
The predicted salary is between 60000 - 84000 £ per year.
£80,000-£120,000 + Benefits Depending on Experience
London with Flexible Working
Are you passionate about building cutting-edge AI solutions that drive real business impact? Do you want to work with some of the world’s leading AI technologies?
Our client helps enterprises harness the power of Generative AI—from crafting meaningful strategies to deploying production-ready AI solutions. As a Applied AI Solution Engineer, you'll be at the forefront of this revolution.
What you’ll do:
- Work hands-on with Python, microservices, distributed systems, and LLMs
- Shape AI strategy, mentor engineers, and drive innovation across multiple projects
- Engage directly with senior stakeholders, explaining complex AI concepts in clear terms
What we’re looking for:
- A track record of delivering scalable AI solutions
- Proven Experience in Large-Scale AI Deployments – Has played a key role in production-ready AI applications
- Expertise in LLMs – Skilled in fine-tuning, training, and prompt engineering
- AI Model Optimization – Strong knowledge of cost management, evaluation, and modification
- Solution Architecture – Can design and build AI solutions from scratch
- Client Engagement – Comfortable working with both technical and non-technical stakeholders
- Team Leadership & Mentorship – Can guide teams, translate high-level ideas into action plans, and drive innovation
StudySmarter Expert Advice🤫
We think this is how you could land AI Solutions Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI technologies, especially around Generative AI and LLMs. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the AI industry through platforms like LinkedIn or relevant meetups. Engaging with others can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving scalable AI solutions. Be ready to explain your role, the challenges faced, and how you overcame them.
✨Tip Number 4
Practice explaining complex AI concepts in simple terms. Since the role involves engaging with both technical and non-technical stakeholders, being able to communicate effectively is crucial.
We think you need these skills to ace AI Solutions Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in enterprise software development and AI solutions. Focus on specific projects where you've delivered scalable AI applications, especially those involving LLMs.
Craft a Compelling Cover Letter:In your cover letter, express your passion for AI and how your background aligns with the role. Mention your experience with Python, microservices, and any leadership roles you've held that demonstrate your ability to mentor and guide teams.
Showcase Relevant Projects:Include a section in your application that details specific projects you've worked on related to AI deployments. Highlight your role in these projects, particularly in areas like model optimization and client engagement.
Prepare for Technical Questions:Anticipate technical questions related to AI concepts and be ready to explain them clearly. Think about how you would communicate complex ideas to both technical and non-technical stakeholders, as this is a key part of the role.
How to prepare for a job interview at MBN Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, microservices, and LLMs in detail. Bring examples of past projects where you successfully delivered scalable AI solutions, as this will demonstrate your hands-on expertise.
✨Communicate Complex Concepts Simply
Since the role involves engaging with senior stakeholders, practice explaining complex AI concepts in layman's terms. This will show your ability to bridge the gap between technical and non-technical audiences.
✨Demonstrate Leadership Experience
Highlight any previous roles where you mentored engineers or led teams. Discuss how you translated high-level ideas into actionable plans, as this aligns with the expectations for team leadership in the position.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in AI deployments and how you overcame them, as this will showcase your critical thinking and adaptability.
