At a Glance
- Tasks: Transform real business problems into practical AI solutions and prototypes.
- Company: Dynamic tech company focused on innovative AI applications.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Fast-paced environment with a focus on experimentation and real-world results.
- Why this job: Be at the forefront of AI innovation and make a tangible impact.
- Qualifications: Strong Python skills and hands-on experience with Generative AI.
The predicted salary is between 50000 - 65000 £ per year.
Location: Hybrid / UK-based
Salary: Competitive
Standard 8 are representing a business looking for an AI Innovation Engineer who can cut through the noise and work out what is actually useful. This is not a "sit in meetings and talk about AI strategy" role. It is for someone who can take a real business problem, explore the right tools, build something that works, and explain whether it is worth taking further. You will be looking at emerging AI products, LLMs, agentic frameworks and automation opportunities, then turning ideas into working proof of concepts quickly. The business wants someone who can move from problem to prototype to recommendation in weeks, not quarters.
Day to day, you will be working with business teams to understand where the pain points are, then translating those into practical AI solutions that engineering teams can build on. Some ideas will be worth scaling. Some will not. Your job is to find out quickly, with evidence, and without getting carried away by hype. You will be hands-on with tools such as OpenAI, Claude, Gemini, LangChain, CrewAI and AutoGen.
Strong Python skills are important, along with experience integrating APIs and pulling together working demos that people can actually use and understand. We are looking for someone with a software engineering or solution architecture background and at least 1-3 years working with Generative AI. You should have built AI proof of concepts before, worked with stakeholders outside of tech, and understand that enterprise AI needs governance, security and commercial sense as much as clever prompts. You do not need to pretend every AI tool is revolutionary. You do need to be curious, practical and quick to learn. The right person will enjoy experimenting, but they will also know when to stop, document what they have found, and recommend a sensible next step. This would suit someone who likes being close to the problem, close to the technology, and close to the decision-making. A builder, not a commentator.
What you'll need:
- Strong Python and API integration experience.
- Hands-on Generative AI experience across LLMs and modern AI tooling.
- Exposure to frameworks such as LangChain, CrewAI or AutoGen.
- A track record of building quick, credible proof of concepts.
- The confidence to speak with business stakeholders and technical teams.
- A practical understanding of AI adoption, governance and enterprise constraints.
Standard 8 are managing applications for this role. Send your CV over and we'll take it from there.
AI Innovation Engineer / AI Solutions Engineer in Manchester employer: Standard 8
Join a forward-thinking company that values innovation and hands-on problem-solving in the rapidly evolving field of AI. With a hybrid work model based in the UK, you'll enjoy a collaborative culture that encourages experimentation and quick learning, alongside competitive salary packages and opportunities for professional growth. This role offers the unique advantage of working closely with both business and technical teams to create impactful AI solutions, making it an ideal environment for those who thrive on building and delivering real-world applications.
StudySmarter Expert Advice🤫
We think this is how you could land AI Innovation Engineer / AI Solutions Engineer in Manchester
✨Tip Number 1
Get hands-on with the tools! Familiarise yourself with OpenAI, Claude, and LangChain before your interview. Show us that you can not only talk about AI but also demonstrate how you've used these tools to solve real problems.
✨Tip Number 2
Prepare to discuss your past projects. We want to hear about the proof of concepts you've built and how you tackled challenges. Be ready to explain your thought process and the impact of your solutions on the business.
✨Tip Number 3
Practice your communication skills! You’ll need to bridge the gap between tech and business teams. Make sure you can clearly articulate complex AI concepts in a way that stakeholders can understand and appreciate.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we love seeing candidates who take the initiative!
We think you need these skills to ace AI Innovation Engineer / AI Solutions Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of AI Innovation Engineer. Highlight your hands-on experience with Generative AI, Python skills, and any proof of concepts you've built. We want to see how you can cut through the noise and deliver practical solutions!
Showcase Your Projects:Include specific examples of projects where you've tackled real business problems using AI tools. We love seeing how you've moved from problem to prototype quickly, so don’t hold back on the details that show your impact!
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity over jargon. Explain your thought process and how you approach AI challenges without getting lost in technical terms. Remember, we’re looking for builders, not just commentators!
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 you’re keen to join our team at StudySmarter!
How to prepare for a job interview at Standard 8
✨Know Your Tools Inside Out
Make sure you’re familiar with the AI tools mentioned in the job description, like OpenAI and LangChain. Be ready to discuss how you've used them in past projects or how you would apply them to solve real business problems.
✨Showcase Your Prototyping Skills
Prepare to talk about specific proof of concepts you've built. Highlight your process from identifying a problem to creating a working demo, and be ready to explain the rationale behind your decisions.
✨Communicate Clearly with Stakeholders
Practice explaining complex AI concepts in simple terms. You’ll need to demonstrate that you can bridge the gap between technical teams and business stakeholders, so think of examples where you’ve done this successfully.
✨Be Ready to Discuss Governance and Practicality
Understand the importance of AI governance and security in enterprise settings. Be prepared to discuss how you balance innovation with practical constraints, and share your thoughts on when to scale an idea or when to pivot.
