Our client, a software engineering–led education technology firm, had previously partnered with us on product development and software engineering roles. As they moved to integrate AI into their business, they needed to make their first strategic AI hire: a Principal Agentic AI Engineer brought on via a 6-month contract with the view to going permanent.This role was designed to evaluate internal business processes, uncover inefficiencies, and explore how technologies like LLMs (Large Language Models) and LLPs (Large Language Processes) could be used to streamline operations and enhance their product offering. The goal was to reduce day-to-day labour costs through AI-led automation and set the foundation for long-term innovation.The ideal candidate needed an advanced data science background, hands-on experience with predictive analytics, and strong technical proficiency across tools including:LangchainAzure OpenAISemantic modelsAzure Data FabricA deep understanding of Microsoft-focused environmentsGiven the emerging nature of Agentic AI, the client recognised this as a niche role with a limited candidate pool.
Our solution
With Agentic AI still in its early adoption phase, sourcing top-tier talent posed a unique challenge. Our recruitment strategy combined:Direct outreach via the consultant’s extensive personal networkUtilisation of non-traditional sourcing channelsCareful screening and consultation to assess real-world experience with AI deployment, not just academic knowledgeFrom a small, highly targeted talent pool, we shortlisted four candidates and facilitated three interview rounds. The client was so impressed by the talent that they considered hiring both finalists. Ultimately, one candidate was selected for a 6-month contract, with the intention of converting the role to permanent.From intake to offer, the end-to-end hiring process for this highly niche role took just 2.5 weeks.
Client’s return on investment
While it's still early days, the client is already seeing signs of added value from bringing on their first AI specialist. The engineer has begun exploring key areas where AI and automation could reduce manual workload, streamline internal processes, and enhance their product's capabilities.Initial assessments suggest strong potential for:Improving operational efficiency through targeted AI integrationReducing ongoing labour costs via automation of routine tasksEnhancing user experience by embedding intelligent features into the platformLaying the groundwork for long-term innovation in line with business strategyBy securing a highly niche and in-demand skill set in just 2.5 weeks, the client gained a strategic advantage, positioning themselves to move quickly in a rapidly evolving space, without compromising on quality.
