At a Glance
- Tasks: Develop and support innovative AI solutions that drive business success.
- Company: Join JD Sports, a leading global retailer in sports fashion and outdoor gear.
- Benefits: Enjoy staff discounts, personal development opportunities, and a vibrant work culture.
- Other info: Collaborate with talented teams and grow your career in a fast-paced industry.
- Why this job: Be at the forefront of AI technology and make a real impact in a dynamic environment.
- Qualifications: 2-3 years in AI or ML engineering with strong Python skills.
The predicted salary is between 80000 - 98000 £ per year.
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. JD Sports Fashion Plc was listed on the London Stock Exchange in 1996 and has been a FTSE100 publicly quoted company since 2019. We want to be the leading global omnichannel retailer in the sports and outdoor industry.
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.
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
- 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.
