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- Tasks: Develop and support cutting-edge AI solutions with a focus on generative AI.
- Company: Join a leading tech group driving innovation in AI.
- Benefits: Competitive salary, flexible work options, and opportunities for skill development.
- Other info: Collaborative environment with great potential for career growth.
- Why this job: Make an impact by building AI systems that transform business processes.
- Qualifications: 2-3 years in AI or software engineering with strong Python skills.
The predicted salary is between 45000 - 55000 ÂŁ per year.
The AI Engineer is responsible for developing, deploying and supporting production‑grade AI and generative AI solutions across JD Group. Reporting into the Head of Data Science & AI, the role focuses on hands‑on engineering delivery of AI systems, including LLM‑based applications, retrieval‑augmented generation pipelines and supporting AI services. Working closely with Senior AI Engineers, Senior Data Scientists, Data Engineering, Platform and Product teams, the AI Engineer contributes to the build and operation of scalable, secure and cost‑effective AI solutions embedded into core business processes. This role sits between Junior and Senior AI Engineer, with increasing accountability for solution delivery, production readiness and technical decision‑making within defined problem areas.
Responsibilities:
- AI Solution Development
- Design, build and support AI and GenAI solutions under the guidance of Senior AI Engineers
- Develop LLM‑based applications, RAG pipelines and AI services using established architectures and patterns
- Implement inference pipelines, APIs and microservices to support AI‑driven use cases
- Contribute to technical decisions within defined components or services
- Production Readiness, LLMOps & MLOps
- Support deployment of AI systems into production environments
- Implement monitoring, logging and basic observability for AI services
- Ensure code, configurations and pipelines are version‑controlled, tested and documented
- Follow established LLMOps, MLOps and CI/CD standards and practices
- Assist with performance optimisation, cost management and reliability improvements
- Governance, Risk & Responsible AI
- Build AI systems in line with responsible AI principles, security and data protection requirements
- Support model evaluation, testing and quality assurance activities
- Ensure AI services comply with agreed governance, auditability and risk controls
- Collaboration & Stakeholder Engagement
- Work closely with Senior Data Scientists to support productionisation of AI‑driven analytical and decisioning solutions
- Collaborate with Data Engineering, Platform and DevOps teams as part of delivery squads
- Communicate technical concepts, progress and risks clearly within the delivery team
- Support Product and Engineering teams in integrating AI capabilities into applications and workflows
- Learning & Capability Development
- Continuously develop skills in AI engineering, generative AI, cloud platforms and modern engineering practices
- Learn from Senior AI Engineers through design reviews, code reviews and delivery feedback
- Contribute to shared components, documentation and reusable assets as capability grows
- Stay informed on developments in AI tooling and platforms, applying learning where appropriate
Role Objectives & KPIs
- Deliver high‑quality AI engineering outputs that support production AI solutions
- Successful contribution to end‑to‑end delivery of AI initiatives
- Reliability, performance and maintainability of AI services owned
- Adherence to engineering, security and governance standards
- Positive feedback from Senior AI Engineers and delivery stakeholders
- Demonstrated progression in technical capability, autonomy and delivery ownership
Skills and Experience:
- 2-3 years experience in AI Engineering, ML Engineering or Software Engineering roles
- Practical experience building and supporting AI or ML‑driven applications
- Good Python skills and experience developing backend services or pipelines
- Understanding of LLMs, generative AI concepts and RAG patterns
- Experience working with cloud platforms, with GCP preferred
- Familiarity with CI/CD, version control and modern engineering practices
- Ability to work collaboratively in cross‑functional teams
- Experience in large‑scale, multi‑brand, or global enterprises; retail experience is advantageous
- Curious, delivery‑focused and keen to learn
AI Engineer in Bury employer: JD Sports
Contact Detail:
JD Sports Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in Bury
✨Network Like a Pro
Get out there and connect with people in the AI field! Attend meetups, webinars, or industry events. You never know who might have a lead on your dream job or can give you insider tips on landing that AI Engineer role.
✨Show Off Your Skills
Create a portfolio showcasing your AI projects, especially those involving LLMs and generative AI. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and understanding of AI concepts. Practice coding challenges and be ready to discuss your past projects. Confidence and clarity in explaining your thought process can really impress interviewers!
✨Apply Through Our Website
Don’t forget to check out our job listings on the StudySmarter website! Applying directly through us not only shows your interest but also helps you stay updated on new opportunities tailored for AI Engineers like you.
We think you need these skills to ace AI Engineer in Bury
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Engineer role. Highlight your experience with AI solutions, Python, and any relevant projects you've worked on. We want to see how you can contribute 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 engineering and how your background aligns with our needs. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Projects: If you've worked on any AI or ML projects, make sure to mention them in your application. Whether it's a personal project or something from a previous job, we want to see what you've built and how you approached problem-solving.
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 StudySmarter family!
How to prepare for a job interview at JD Sports
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and generative AI concepts. Be ready to discuss LLMs, RAG pipelines, and how you've applied these in past projects. Showing that you understand the technical details will impress the interviewers.
✨Showcase Your Collaboration Skills
Since this role involves working closely with various teams, be prepared to share examples of how you've successfully collaborated in cross-functional settings. Highlight any experiences where you communicated technical concepts clearly or contributed to team projects.
✨Demonstrate Problem-Solving Abilities
Think of specific challenges you've faced in AI engineering and how you overcame them. Discuss your approach to deploying AI systems and ensuring production readiness, as well as how you handle performance optimisation and reliability improvements.
✨Stay Updated and Curious
Show your enthusiasm for continuous learning in the AI field. Mention any recent developments in AI tooling or platforms that you've explored. This demonstrates your commitment to growth and staying current in a rapidly evolving industry.