A case study on how Jack Ashley partnered with a leading global private equity firm to appoint a Head of AI Platforms, a newly created role designed to accelerate AI adoption across the organisation. Through a targeted, research-led search of senior AI and applied LLM leaders, Dartmouth delivered a focused shortlist from a highly specialised global talent pool, resulting in the successful placement of a leader able to combine deep technical expertise with strategic vision.
The firm focuses on active ownership and long-term value creation, partnering with management teams across its portfolio to drive operational improvement, digital transformation and sustainable growth.
As part of its continued investment in technology and data capabilities, the firm created a new leadership role within its AI platforms function to support the development and application of artificial intelligence across the organisation.
The firm sought to appoint a Head of AI Platforms to provide hands-on leadership for its AI engineering capability.
While strong engineering expertise was already in place, the organisation required a senior leader who could set the strategic vision, accelerate adoption of AI technologies and guide key architectural decisions across areas such as large language models (LLMs), LangChain, LangSmith and Snowflake.
Crucially, the role required someone who could combine deep technical credibility with the ability to communicate effectively with non-technical stakeholders. The successful candidate would need to translate complex AI capabilities into practical business applications, helping position the organisation at the forefront of pragmatic AI adoption within private equity.
Given the highly specialised nature of the role and the limited global talent pool operating at the intersection of AI engineering, platform development and enterprise adoption, the firm engaged Dartmouth to support a targeted search.
Given the niche nature of the brief, we approached the search as a highly targeted and research-led process.
We mapped senior AI and applied LLM leaders across private equity, high-growth technology companies and advanced engineering environments, focusing on individuals who combined deep technical expertise with the ability to influence senior stakeholders.
Particular attention was given to candidates who had built or scaled AI platforms, made deliberate tooling and architecture decisions, and demonstrated the ability to translate emerging AI developments into tangible commercial outcomes.
Throughout the search, we maintained close calibration with the client to refine the profile and ensure alignment on both technical capability and leadership style.
The process began with a full market map and compensation benchmarking exercise to align on the scope of the role and the competitiveness of the package. A detailed scorecard was then developed and agreed upon early in the process, providing clear evaluation criteria and ensuring a structured and consistent interview process.
The search was delivered through a structured, data-led process that produced a calibrated longlist of 24 high-calibre candidates across two locations.
From this group, 8 candidates progressed to interview, with 3 candidates advancing to the final stage of the process.
Following a four-stage interview process, the mandate concluded with a successful offer and acceptance, securing a high-impact leader for the newly created Head of AI Platforms role.
The appointment of a Head of AI Platforms represented a strategically important step in the firm’s broader technology and data strategy.
Artificial intelligence is rapidly becoming a core enabler of operational improvement, insight generation and competitive advantage across private equity portfolios. Appointing a leader who could bridge cutting-edge AI engineering with practical business application was, therefore, critical.
Beyond the immediate role, the search helped the client better understand the emerging global talent pool of AI platform leaders and how those individuals are shaping the application of AI within investment organisations. The process provided valuable market insight into compensation benchmarks, skill set availability and the evolving expectations placed on AI leadership roles within private equity.
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