Head of Applied AI

Head of Applied AI Location: Our offices are in Central London, along with several of our customers. Travel to our customer sites is required, the frequency of which will vary from customer-to-customer. You need to be able to travel onsite to London up to 3 days per week, although onsite requirements will vary week-to-week and customer-to-customer from 0 to 3 days. Salary: Competitive (DOE) Defence/SC Clearance Requirements: SC clearance is required for our customer facing teams. You do not need active SC clearance as we will undertake checks upon you joining, but you must be eligible to pass SC clearance. DV clearance may be required for certain roles, so the ability/willingness to pass DV clearance is advantageous but not essential. About Cloudscaler Cloudscaler is a rapidly growing cloud consultancy. We partner with ambitious enterprise and public sector customers to design, build, operate, and support secure, governed cloud platforms that meet the highest regulatory and industry standards. We are scaling deliberately. Our revenue ambition depends on deploying the right people onto the right work quickly, and on making disciplined use of our capacity. This role is central to that.   About the role Cloudscaler's Applied AI business unit launched at the start of 2026 and has grown quickly, with an established offering, live client engagements and a pipeline in place. The current Head of Applied AI is stepping back from the role for personal reasons and remains with the business to hand over, so the incoming Head inherits a running unit rather than a standing start. We are recruiting to take it into its next phase of growth. The work is running; the structure is not yet. Offerings are defined, collateral exists, engagements are live and Cloudscaler's public voice on applied AI is established. What does not yet exist is the shape around it: there is no ring-fenced team, no separate P&L and no formally defined roles. The unit began with strategy, technical expertise and sales all held in one place. Technical capability has grown since; strategy and commercial ownership have not. Formalising the practice - defining the team, the roles and the commercial structure - is part of the job rather than something the incoming Head inherits finished. This role has both external and internal responsibilities: Externally, it owns our AI go-to-market offerings and the customer, partner and pre-sales activity that turns them into pipeline, and it is Cloudscaler's public voice on applied AI. Internally, it carries full commercial accountability for the business unit, provides technical delivery oversight, builds and leads the practice, and is accountable for enabling the whole company to work with AI. The role reports to the CTO and works closely with leadership across the business. The person needs to be technical enough to direct and challenge the engineering work, and commercially credible enough to scale the unit and its offering. It is a hands-on role. In one week, you might write a business case for the Leadership Team, advise a client CTO on their AI strategy, review an engineer's architecture decision and speak at a conference on what we have learned. External responsibilities These responsibilities are customer-facing, partner-facing and public facing: Relentless client focus - Maintaining a relentless client focus, calibrated to how mature the business unit is, and being decisive about where to concentrate effort and what to stop. Early on that means client meetings and pipeline growth; later it means shifting weight to larger, more sustainable areas of demand. AI go-to-market offerings - Defining and owning our AI go-to-market offerings, working with sales to take them to market. For each offering, defining what it is, who buys it, the problem it solves, its indicative price and its delivery model, and reviewing the set as the market moves, retiring what no longer sells and evolving what does. Customer