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- Tasks: Design and deploy AI solutions that create real business value and enhance customer experiences.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Enjoy a competitive salary, health perks, remote work options, and growth opportunities.
- Other info: Dynamic hybrid role with opportunities for continuous learning and career advancement.
- Why this job: Be at the forefront of AI technology and make a tangible impact in the industry.
- Qualifications: Degree in relevant field and experience in AI or machine learning development.
The predicted salary is between 60000 - 80000 £ per year.
Location: UK-based hybrid role, occasional travel to site.
Day to day:
- Design, build and deploy AI and machine learning solutions that deliver measurable customer and business value.
- Develop, train and optimise machine learning and generative AI models for use in production systems.
- Build and operate scalable data pipelines, model training workflows and inference services using cloud-native and managed AI platforms.
- Collaborate with product managers, engineers and data teams to translate business problems into effective AI solutions.
- Own the quality, performance and reliability of AI solutions, including monitoring, retraining and continuous improvement.
- Implement responsible AI practices, ensuring solutions meet security, privacy, governance and ethical standards.
- Evaluate and select appropriate AI tools, models and platforms, making build vs buy recommendations where appropriate.
- Support live AI services by investigating incidents, analysing model behaviour and resolving production issues.
- Continuously explore and apply new AI techniques, frameworks and approaches where they deliver clear benefit.
- Take ownership for delivering agreed outcomes, raising risks early and contributing to team delivery and learning.
What we need from you:
- Degree in Computer Science, Data Science, Engineering or related discipline, or equivalent practical experience.
- Several years in software engineering with at least 2 to 3 years developing AI or machine learning solutions in production environments.
- Experience integrating AI models into enterprise platforms and customer-facing systems.
- Strong capability in machine learning frameworks, data modelling and API based integration.
- Ability to translate business problems into AI solutions, understanding of data governance, model evaluation and ethical considerations.
- Demonstrated experience working as an AI or machine learning engineer delivering models or AI services into production.
- Strong experience with modern machine learning and/or generative AI frameworks.
- Experience working with large language models, either through fine-tuning open source models or integrating with managed foundation model platforms.
- Hands-on experience building data pipelines and model workflows using tools such as Python, SQL, Spark or similar data processing technologies.
- Experience deploying and operating AI systems in cloud environments using containerisation, managed ML services or serverless architectures.
- Understanding of MLOps practices including model versioning, experiment tracking, CI/CD for models and monitoring of model performance and drift.
- Experience applying responsible AI principles, including data privacy, bias mitigation, explainability and security controls.
- Ability to analyse complex problems, experiment iteratively and translate findings into robust engineering solutions.
- Strong collaboration and communication skills, with the ability to work effectively across engineering, product and data teams.
- A growth mindset with curiosity for emerging AI technologies and a focus on practical, value-driven outcomes.
Core Competencies & Technical Skills:
- Ability to design, integrate and operate AI enabled solutions within enterprise environments, including prompt-driven workflows, retrieval-augmented systems and AI agents, applying structured evaluation, testing and monitoring practices to ensure AI outputs are reliable, secure and compliant with organisational guardrails.
- Prepares and manages data used in AI workflows and takes responsibility for the responsible lifecycle of AI features from experimentation through to deployment and continuous improvement.
AI Software Engineer employer: Centrica
Contact Detail:
Centrica Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Software Engineer
✨Network Like a Pro
Get out there and connect with folks in the AI and software engineering space! Attend meetups, webinars, or even local tech events. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Show Off Your Skills
Create a portfolio showcasing your AI projects and solutions. Whether it's GitHub repos or a personal website, let your work speak for itself. This is your chance to demonstrate your hands-on experience with machine learning frameworks and data pipelines!
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding of AI concepts. Practice common interview questions and be ready to discuss how you've tackled real-world problems with AI solutions. Confidence is key!
✨Apply Through Our Website
Don't forget to check out our careers page and apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Software Engineer role. Highlight your experience with machine learning frameworks, data pipelines, and any relevant projects you've worked on. We want to see how you can bring value to our team!
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 aligns with our mission at StudySmarter. Don’t forget to mention specific examples of your work that demonstrate your problem-solving skills and collaboration with teams.
Showcase Your Projects: If you've got any personal or professional projects related to AI or machine learning, make sure to include them in your application. We love seeing practical applications of your skills, so share links or descriptions of your work that illustrate your capabilities.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!
How to prepare for a job interview at Centrica
✨Know Your AI Stuff
Make sure you brush up on the latest AI and machine learning frameworks. Be ready to discuss your hands-on experience with tools like Python, SQL, and Spark, as well as any large language models you've worked with. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've translated complex business problems into effective AI solutions. Think of a few scenarios where you’ve successfully implemented AI in production environments and be ready to explain your thought process and the outcomes.
✨Understand Responsible AI Practices
Familiarise yourself with responsible AI principles, including data privacy and bias mitigation. Be prepared to discuss how you ensure that your AI solutions meet security, privacy, and ethical standards. This shows you’re not just technically savvy but also socially aware.
✨Collaboration is Key
Since this role involves working closely with product managers, engineers, and data teams, think of examples that highlight your collaboration and communication skills. Be ready to share how you’ve contributed to team projects and how you handle feedback and challenges.