AI Engineer

The Premier League

Job Location:

London - UK

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

The Premier Leagues IT department is looking for an experienced AI Engineer to join the Engineering team led by the Head of Systems responsible for designing building and supporting AI-powered copilots and agents across the Premier League and its member clubs.

The AI Engineering functions core responsibility is to design build deploy and maintain intelligent agents and copilots that enhance productivity automate workflows and enable smarter decision-making across the organisation and its member clubs.

This role will work closely with business stakeholders to identify opportunities where AI agents can deliver value and lead the implementation of those solutions at scale.

Who we are

The Premier League is home to some of the most competitive and compelling football in the world. The League and its Clubs use the power and popularity of the competition to inspire fans communities and partners in the UK and across the world. The Premier League brings people together from all backgrounds. It is a competition for everyone everywhere and is available to watch in over 900 million homes in 189 countries.

We have a wide variety of responsibilities. These include organising the competition and its Handbook as well as managing the centralised broadcast and commercial rights. The work we do in conjunction with the Clubs also goes far beyond the 90 minutes. We support and provide a framework for youth development we protect the organisations intellectual property support the wider game and community programmes undertake international development work and liaise with governing bodies and other leagues.

The Premier League is an equal opportunities employer and strives to create an inclusive culture where talent can flourish. We believe in the potential of everyone and open our doors to those who share those values. All appointments will be made based on merit; however we particularly encourage applications from women people from minority ethnic communities LGBTQ people and disabled people.

Our hybrid-working model also allows you some variety on your place of work offering you the chance to work from home on some days each week. Where possible you will attend the office or site visits in line with our company policy. All staff liaise closely with their line manager to manage their time appropriately and according to their work and team requirements.

Key Responsibilities

Design and implement scalable reliable AI agents and copilots using modern LLM frameworks. Define patterns for orchestration tool usage memory and human-in-the-loop workflows. Provide technical governance and best practices for agent-based systems.
Strong experience working with large language models (e.g. OpenAI Azure OpenAI) prompt engineering embeddings vector databases and retrieval-augmented generation (RAG). Ability to evaluate and optimise model performance for real-world use cases.
Build agents that integrate with internal systems (APIs databases SaaS tools such as Microsoft 365 Notion etc.) to automate workflows and enhance productivity.
Design intuitive copilot experiences that augment users rather than replace them with a focus on usability trust and explainability.
As a senior member of a growing team support other engineers through mentoring documentation and establishing best practices in AI engineering.
Define metrics and evaluation frameworks for agent performance reliability and safety. Continuously iterate based on feedback and usage data.
Experience deploying AI systems into production environments including monitoring observability cost control and lifecycle management of models and agents.
Experience of working within a project team in an Agile manner collaborating closely with stakeholders to iteratively deliver value.
Ensure AI solutions adhere to security privacy and data governance standards. Awareness of risks such as hallucination data leakage and misuse with mitigation strategies in place.
Liaise with the relevant Business Analyst Quality Assurance Team Security Team Infrastructure Team and stakeholders on matters as required.

Role Requirement

Experience building AI agents copilots or automation workflows using LLMs in a production or enterprise environment.
Strong understanding of prompt engineering RAG architectures and tool-augmented agents.
Experience integrating AI solutions with APIs databases and enterprise systems.
Familiarity with TypeScript.
Education in an appropriate field of study or equivalent work experience.
Experience of leading projects or owning AI-driven initiatives end-to-end.
Experience of managing matters autonomously.
Strong technical awareness and the ability to think strategically about AI adoption within an organisation.
Outstanding attention to detail and strong analytical and research skills.
Excellent written and verbal communication skills with the ability to explain AI concepts to non-technical stakeholders.
Excellent work ethic and ability to cope with pressurised situations and tight timeframes whilst maintaining a professional approach.

Our commitment to safeguarding includes implementing robust safer recruitment procedures to assess the suitability of individuals applying for roles that involve work with children and adults who are or may be at risk of harm. For further information please see our Safeguarding Policy and Safer Recruitment Guidance.

To apply please visit our careers page and apply with your CV and a cover letter. The closing date for applications is 5 June 2026.

We will remove barriers that prospective candidates might face at any stage of our recruitment process. If you have a disability and would like the advert in an alternative format or would like to talk about how we can adjust the interview process to best support you please contact .

Required Experience:

This role will work closely with business stakeholders to identify opportunities where AI agents can deliver value and lead the implementation of those solutions at scale.

Who we are

Key Responsibilities

Design and implement scalable reliable AI agents and copilots using modern LLM frameworks. Define patterns for orchestration tool usage memory and human-in-the-loop workflows. Provide technical governance and best practices for agent-based systems.
Strong experience working with large language models (e.g. OpenAI Azure OpenAI) prompt engineering embeddings vector databases and retrieval-augmented generation (RAG). Ability to evaluate and optimise model performance for real-world use cases.
Build agents that integrate with internal systems (APIs databases SaaS tools such as Microsoft 365 Notion etc.) to automate workflows and enhance productivity.
Design intuitive copilot experiences that augment users rather than replace them with a focus on usability trust and explainability.
As a senior member of a growing team support other engineers through mentoring documentation and establishing best practices in AI engineering.
Define metrics and evaluation frameworks for agent performance reliability and safety. Continuously iterate based on feedback and usage data.
Experience deploying AI systems into production environments including monitoring observability cost control and lifecycle management of models and agents.
Experience of working within a project team in an Agile manner collaborating closely with stakeholders to iteratively deliver value.
Ensure AI solutions adhere to security privacy and data governance standards. Awareness of risks such as hallucination data leakage and misuse with mitigation strategies in place.
Liaise with the relevant Business Analyst Quality Assurance Team Security Team Infrastructure Team and stakeholders on matters as required.

Role Requirement

Experience building AI agents copilots or automation workflows using LLMs in a production or enterprise environment.
Strong understanding of prompt engineering RAG architectures and tool-augmented agents.
Experience integrating AI solutions with APIs databases and enterprise systems.
Familiarity with TypeScript.
Education in an appropriate field of study or equivalent work experience.
Experience of leading projects or owning AI-driven initiatives end-to-end.
Experience of managing matters autonomously.
Strong technical awareness and the ability to think strategically about AI adoption within an organisation.
Outstanding attention to detail and strong analytical and research skills.
Excellent written and verbal communication skills with the ability to explain AI concepts to non-technical stakeholders.
Excellent work ethic and ability to cope with pressurised situations and tight timeframes whilst maintaining a professional approach.