JOB DESCRIPTION SUMMARY

Title: AI Optimisation Manager
LOCATIONS: Leeds or Bristol
WORKING PATTERN: Hybrid, 40% (or two days) in an office location

JOB DESCRIPTION

The AI Optimisation Manager will work as part of virtual optimisation squads across our Centres of Excellence, Platform and Operations teams to lead the design and delivery of AI-enabled HR solutions that enhance colleague experiences, streamline operations and support strategic workforce initiatives.
The ideal candidate will have a deep knowledge of AI (e.g. chatbots, predictive analytics, intelligent and autonomous agents) and automation, demonstrating a proven track record of identifying and capitalising on opportunities to implement this technology effectively within the HR function. They will act as a key enabler for fostering innovation and ensuring the successful identification and delivery of AI solutions, across our HR operational products and services.
We highly value external insights and encourage candidates who bring a fresh, outside-in perspective and demonstrate a strong willingness to learn and the capacity to grasp and quickly absorb emerging concepts such as Agentic AI.

Continuous Learning:

• Commitment to staying abreast of the latest developments in Agentic AI and related technologies, continuously seeking ways to improve and optimise their application

THE ROLE WILL BE VARIED, NO TWO DAYS WILL BE THE SAME, AND YOU’LL BE CONCURRENTLY DELIVERING ACROSS A RANGE OF RESPONSIBILITIES INCLUDING:

Process Redesign:

• Identifying inefficiencies in current processes and redesigning them using internal SCALE methodology and automation techniques. This involves mapping out current processes, identifying bottlenecks and waste, and developing efficient future state processes that leverage the latest tech and best practices.

Data-Driven Decision Making:

• Applying data-driven insights to diagnose issues and inform transition planning. Using analytics to uncover patterns, predict outcomes, and guide decision-making to ensure optimisation efforts are grounded in solid evidence.

Opportunity identification:

• Conduct thorough needs assessments to identify and understand pain points and working with technical teams to determine which AI solutions will provide the most value in addressing these challenges, while incorporating impactful human touch at critical moments.

Workshop Facilitation & Stakeholder Engagement:

• Challenging stakeholders to adopt simple, scalable designs that align with business goals. Facilitate workshops, lead discussions, and build consensus among diverse groups to drive forward the optimisation and AI automation agenda.

Innovation Fostering:

• Foster a culture of innovation by promoting the adoption of AI technologies. Continuously research and evaluate modern technologies, such as Agentic AI, to ensure our approach remains innovative and effective.
• Collaborate with our architecture and specialist engineering teams to implement these advancements.

External Insight and Market insights:

• Leverage a strong network to stay updated on AI trends and to understand how other market players are tackling similar challenges.
• Bringing innovative ideas and best practices into our initiatives. Effectively communicate these insights externally through compelling storytelling.

Continuous Learning:

• Commitment to staying abreast of the latest developments in Agentic AI and related technologies, continuously seeking ways to improve and optimise their application.

Enabler Identification:

• Identifying the broad range of enablers needed to successfully implement new optimised processes. This includes technology, organisation design, training, communication, and other elements that support optimisation efforts.

Transition Monitoring:

• Monitoring transition progress, addressing resistance, and embedding continuous improvement.
• Track the implementation of new processes, identify and mitigate risks, and ensure that changes are fully embedded and sustained over time.

Delivering at Pace:

• Leading initiatives with urgency and efficiency, ensuring timely delivery of optimisation projects.
• Use agile working practices to drive opportunities and designs of AI solutions at pace, employing an iterative approach.