At a Glance
- Tasks: Build scalable AI solutions and data pipelines that drive real business value.
- Company: Join a forward-thinking tech team transforming industries with AI and data.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Work at the cutting edge of AI technology and make a tangible impact.
- Qualifications: Experience in AI or data engineering, strong programming skills, and teamwork.
The predicted salary is between 50000 - 70000 € per year.
Position Summary
Our client's AI & Data function focuses on helping organisations solve complex business challenges through the effective use of data, artificial intelligence, and modern technology platforms. The team delivers end-to-end, business-driven solutions that integrate data, technology, and processes across organisations and their wider ecosystems, including partners, suppliers, and customers. The focus is on creating scalable, high-quality, and governed solutions that enable better decision-making, operational efficiency, and digital transformation.
The Opportunity
As an AI Engineer, you will work at the intersection of data, engineering, and artificial intelligence to build practical, scalable solutions that deliver real business value. You'll collaborate with cross-functional teams to design, develop, and deploy data pipelines, machine learning models, and AI-enabled applications that support analytics, automation, and insight generation.
This role suits someone who enjoys:
- Working with modern data and AI technologies
- Delivering clean, reliable, production-ready solutions
- Translating business needs into technical outcomes
Key Responsibilities
- Data Engineering & Development
- Design, build, and maintain scalable data pipelines, datasets, and data models
- Support analytics, reporting, and AI-driven use cases
- Work with both structured and unstructured data sources
- AI & Machine Learning
- Develop and deploy machine learning models for:
- Prediction
- Classification
- Automation
- Insight generation
- Support the full life cycle from experimentation through to production
- Generative AI & LLM Applications
- Develop AI-powered solutions using large language models (LLMs)
- Apply prompt engineering and context engineering techniques
- Build use cases such as:
- Chatbots
- Document processing
- AI copilots
- Workflow automation
- Integrate data from multiple internal and external sources
- Ensure data quality, consistency, and reliability across platforms
- Work closely with:
- Business Analysts
- Data Analysts
- Product teams
- Translate business requirements into scalable technical solutions
- Communicate technical concepts clearly to non-technical stakeholders
- Implement testing, validation, and monitoring processes
- Ensure:
- Data accuracy
- Model performance
- System reliability
- Optimise pipelines, storage, and models for performance and scalability
- Produce clear technical documentation (pipelines, models, logic)
- Follow best practices around:
- Data governance
- Security
- Privacy
- Compliance
Skills & Experience
Essential
- Experience in a similar role (AI Engineer, Data Engineer, Machine Learning Engineer, or Data Developer)
- Strong programming skills (Python, SQL or similar)
- Experience building and maintaining data pipelines
- Working with structured and unstructured data
Desirable
- Experience with machine learning frameworks (e.g. TensorFlow, PyTorch, scikit-learn)
- Exposure to Generative AI tools/frameworks (e.g. LLMs, LangChain)
- Experience with cloud platforms (Azure, AWS, or GCP)
- Familiarity with data platforms, data warehouses, or big data technologies
Soft Skills
- Strong analytical and problem-solving ability
- Attention to detail and commitment to quality
- Ability to communicate technical ideas effectively
- Experience working in Agile environments
Additional Requirements
Candidates may be required to undergo background checks or security clearance depending on client/project requirements.
About the Team
You’ll be working within a collaborative technology and data environment focused on delivering transformation for clients across multiple industries. The team combines deep technical expertise with innovative thinking to help organisations modernise their data and AI capabilities, unlock value, and improve outcomes for customers, employees, and stakeholders.
AI Engineer in Manchester employer: Hays Technology
As an AI Engineer with our client, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. The company offers exceptional employee growth opportunities through exposure to cutting-edge technologies and projects that drive real business impact, all while being part of a supportive team dedicated to transforming data and AI capabilities across various industries. Located in a vibrant area, the role provides a unique chance to engage with diverse clients and contribute to meaningful solutions that enhance operational efficiency and decision-making.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in Manchester
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and data space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines or machine learning models. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Don’t be shy about reaching out directly to companies you’re interested in. A quick email or LinkedIn message expressing your enthusiasm for their work can go a long way. Plus, it shows initiative, which is always a plus!
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for talented AI Engineers like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace AI Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with data pipelines, machine learning models, and any relevant technologies. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Keep it concise but impactful – we love a good story!
Showcase Your Projects:If you've worked on any cool projects related to AI or data engineering, make sure to mention them! Whether it's a personal project or something from a previous job, we want to see your hands-on experience and creativity.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our awesome team at StudySmarter!
How to prepare for a job interview at Hays Technology
✨Know Your Tech Inside Out
Make sure you’re well-versed in the programming languages and frameworks mentioned in the job description, like Python and TensorFlow. Brush up on your data pipeline skills and be ready to discuss how you've built and maintained them in past roles.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges or developed machine learning models. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your analytical abilities.
✨Communicate Clearly with Non-Techies
Since you'll be translating technical concepts for non-technical stakeholders, practice explaining your projects in simple terms. This will demonstrate your ability to bridge the gap between tech and business needs.
✨Be Ready for Practical Tests
Expect to face practical assessments or coding challenges during the interview. Brush up on your coding skills and be prepared to solve problems on the spot, showcasing your thought process and approach to problem-solving.
