How Aspire Life Sciences helped a medical imaging company secure a technical leader, and make a second complementary hire from the same search.
What happens when an AI team’s ambitions outgrow the data infrastructure supporting it?
For an established medical imaging company, the next step in developing its AI capabilities required someone to take ownership of the data foundations beneath its models.
Taylor Lyons at Aspire Life Sciences identified a technical leader who could build that function. The search also introduced a second candidate whose strengths suited a complementary AI integration role, resulting in two appointments.
The challenge: giving data a clear owner
The company already had AI engineers developing models for its medical imaging products. However, no single person owned how image data was stored, structured, versioned, checked and made available to the team.
Engineers were spending valuable time managing and preparing data themselves. As the company invested in its AI, cloud and digital capabilities, it needed a more consistent foundation to support further development.
The newly created lead role would establish that foundation, giving engineers better access to reliable datasets and greater clarity about the data used in experiments and model releases.
The brief: technical leadership across disciplines
Finding the right person required a precise understanding of the role.
The client needed expertise in large-scale data platforms, pipelines, metadata, quality and governance, alongside an understanding of how these capabilities support AI development.
The leadership requirement was equally specific. This person would set technical direction, collaborate across engineering teams and build a new function. Leading a large team was not the central responsibility.
The largely remote arrangement also required someone willing to visit the company’s headquarters regularly to work with colleagues in person.
The search: connecting capability with motivation
Taylor Lyons approached a candidate directly after identifying his profile. Already known to Aspire, he had not applied for the position and had no existing relationship with the client.
He brought approximately a decade of data engineering experience, including leadership of cross-functional engineering teams, high-volume data platforms and complex migrations where continuity was critical. His background also covered data quality, governance, real-time pipelines and technologies used in modern AI environments.
Understanding his motivation was just as important.
After several years with the same employer, he wanted greater technical ownership and the opportunity to shape a function without moving into a conventional people-management role.
The client’s brief offered that next step. Moving into medical technology added further appeal, distinguishing the opportunity from the other interview processes he was pursuing.
Demonstrating the fit
Two candidates progressed to the final stage and met the leadership and technical teams in person.
For the successful lead candidate, that meeting demonstrated how he would approach the challenge. He used a whiteboard to explore ideas for the data environment, engaging directly with the detail of what the company wanted to build.
Client feedback highlighted both his technical contribution and the strength of his fit for the role.
Securing the appointment also required careful discussion of the offer. Taylor worked with the client to explore remuneration structure, remote working arrangements and future salary progression, helping the candidate assess the opportunity as a sustainable career move.
A second appointment from the same search
The other finalist also impressed the client.
Although his experience was less closely aligned with the original data leadership brief, the hiring team recognised its relevance to AI integration. During the interview, the client introduced an alternative engineering opportunity and subsequently progressed him through a separate process.
Both candidates were hired, bringing complementary capabilities into the business: one to establish and own the data foundations, the other to support AI integration across the wider product and engineering environment.
The outcome: ownership and complementary capability
The confirmed result was two appointments from one initial search.
The technical leadership hire gives the company a dedicated owner for dataset organisation, documentation, versioning and quality. The intended benefit is to reduce the time AI engineers spend preparing data and help them focus more consistently on developing models and products.
The second appointment adds expertise to support the integration of AI into the wider engineering environment.
Longer-term operational results remain to be measured. The immediate achievement is clear: the client secured the leadership capability it originally needed and recognised an opportunity to strengthen a second area through the same search.
For Aspire Life Sciences, this engagement demonstrates the value of understanding the business requirement, assessing candidates beyond their job titles and connecting technical capability with the career motivations that make an appointment work.