UK AI Action Plan: 7 AI job roles which will be in high demand
Following the UK government’s announcement about plans to use AI across the UK to boost growth and deliver more efficient services, we speak to chief technology officer at Redcentric, Paul Mardling, to get his thoughts on the 7 AI roles we could expect to see emerging over the coming months and years.
1. Chief knowledge officers
Large language models (LLM) and similar technologies require highly curated and unstructured data sets – these are essentially human readable texts. I’d expect knowledge management and curation to become an important role for businesses and organisations, with the likely emergence of chief knowledge officers as new and important roles.
2. AI agent engineers and developers
AI agents will be an important part of AI implementations. Whilst in principle, AI can build more AI, in this iteration I’d expect specialist engineers and developers to emerge with the skills for building agents.
3. Model development engineers
At present, the infrastructure and processes for deploying AI models are not very mature. Specialist engineers will be required to deploy custom models efficiently and scalably.
4. AI trainers
It’s likely that specialist roles will be needed for human-in-the-loop training of AI models. These specialists will be particularly important for the training and fine tuning of custom large language models (LLMs).
5. Data scientists and AI experts
At the lowest level, AI experts and data scientists will be required to train custom models and build datasets around structured data for AI training. At the highest level, experts will take on more strategic responsibilities and will need to ensure that AI solutions are ethical and scalable.
6. AI infrastructure architects and engineers
The deployment of large-scale graphical processing units (GPUs) powered AI clusters will require specialist infrastructure architects and engineers to design and build the systems.
7. Cooling systems engineers
Perhaps the largest problem in AI computing is the removal and dissipation of heat. There will be a great need for more engineers with specialist skills in this area.
And finally….Demand for data centres
Greater investment in AI development and implementation is likely to lead to an increased demand for data centres. However, building new data centres is a significant investment. Data centres take time to bring online and require planning permission, power provisioning and physical construction.
In the short term, this will lead to increased demand for existing data centres, many of which haven’t been designed for the density or power draw that AI systems require.
New data centres need to be designed with high power density computing in mind in order to be energy-efficient. This is very different from previous designs which were built around 2-5kW power density racks in halls.
Liquid cooling is essential in racks with greater than 10kW power density and is desirable in the 5-10kW range. Efficient use of excess heat is also likely to emerge, either for thermal regenerative power generation or communal heating projects.
