Director of Application Engineering (AI)

Location: London; hybrid workplace

Company

hirify.global is building an AI-powered biomedical knowledge platform that uses a high-precision Knowledge Graph and GenAI to help researchers and biopharmaceutical organizations interpret scientific publications, clinical trials, regulatory documents, and other complex data.

What you will do

• Lead the engineering teams behind the agentic research product and customer-facing applications through a group of engineering managers.
• Set the application engineering direction, team structure, operating model, and resourcing decisions within the wider engineering strategy.
• Drive predictable delivery with Product through capacity-based planning, roadmaps, cross-functional technical programmes, and explicit trade-offs.
• Own customer outcomes, product quality, security, operational health, release practices, and incident response.
• Manage and coach engineering managers, strengthen the management layer, own hiring, and shape organisational culture.
• Drive AI-first workflows, reusable tooling, standards, and measurable ROI across planning, coding, review, testing, and release.

Requirements

• 10+ years of experience in software engineering and 4+ years leading engineering managers, ideally in a scale-up environment.
• Track record of predictable delivery through capacity-based planning, limiting work in progress, and making trade-offs with Product.
• Customer-first approach focused on measurable customer value rather than feature volume.
• Experience leading teams that build with AI coding agents such as Claude Code or similar, including adapting review, testing, and quality practices when agents write most of the code.
• Experience leading distributed teams across countries and time zones.
• Clear, direct communication with engineers, product leaders, and executives.
• Broad engineering leadership across several sub-domains and the ability to make strategic decisions in areas without deep personal expertise.
• Established use of AI in team workflows and the ability to scale AI-first practices across a function with shared tooling, standards, and measurable return.

Nice to have

• Experience leading teams that ship LLM, ML, or other AI-powered features to production, with sufficient technical depth to challenge architecture and quality decisions.
• Experience in life sciences, biomedical data, or B2B SaaS for enterprise customers.
• Hands-on experience building agentic systems, including multi-step agents, tool use, and evaluation.

Culture & Benefits

• Department-wide impact as part of the engineering leadership team, contributing to engineering-wide decisions and leading engineering when needed.
• Equal opportunity employer committed to fairly considering qualified candidates from all backgrounds.