The Premier League

AI Engineer

• 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.

Business Analyst

• Assess departmental processes and workflows to identify inefficiencies, bottlenecks and opportunities for automation using AI and digital solutions.
• Lead discovery engagements with stakeholders (workshops and 1-2-1 sessions) to understand current-state operations and define future state, AI enabled processes.
• Define project scope, objectives and value cases with a clear focus on automation benefits, ROI and operational impact.
• Document complex business processes (current and future state), including opportunities for AI augmentation or full automation.
• Translate business needs into structured requirements, user stories, process flows, and acceptance criteria, with clear alignment to automation outcomes.
• Evaluate and recommend AI tools, platforms and software solutions suitable for different business functions.
• Build and maintain a prioritised backlog or roadmap of automation and AI opportunities aligned to business value and strategic goals.
• Communicate AI enabled solution designs and transformation opportunities to senior internal and external stakeholders in a clear, accessible way.
• Develop business cases and Statements of Work, incorporating automation strategies, expected efficiencies and implementation approaches.
• Collaborate closely with our development team to ensure solutions are aligned with requirements and maximise automation potential.
• Support implementation, testing (QA/UAT) and adoption of AI driven solutions, ensuring they deliver against expected outcomes.
• Assist with the delivery of training and guidance to business teams to enable adoption of new tools, processes, and AI capabilities.
• Build strong relationships across departments to act as a trusted advisor on process improvement and automation strategy.
• Continuously monitor and evaluate emerging AI technologies to identify new opportunities for the business.