Established in 1981 with a single store in the Northwest of England, the JD Group is a leading omni-channel retailer of Sports Fashion, Outdoors and Gyms with our colleagues working in stores across several retail fascias in many markets around the world.
JD Sports Fashion Plc was listed on the London Stock Exchange in 1996 and has been a FTSE100 publicly quoted company since 2019 and continues to grow in the UK and internationally.
We want to be the leading global omnichannel retailer in the sports and outdoor industry. To be a part of this successful company and help us to achieve this you will have the desire to ingrain our strategic goals of being a people-led, innovative and customer-focused organisation which provides operational excellence whilst identifying new areas of growth as part of our day to day objectives.
AI Engineer
Role Overview:
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
We know our colleagues work tirelessly to make JD Sports the success it is today and in turn, we offer them some amazing benefits including staff Discount On JD Group and other brands within the organisation and personal development opportunities to learn and develop at work.
Thank you for your time
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