Head of Engineering (AI)

Location: London, England; hybrid work

Salary: £140K–£170K per year

Company

hirify.global builds autonomous AI control and optimisation systems that help heavy industrial plants such as cement, steel, and glass facilities operate more efficiently, stably, and with lower carbon emissions.

What you will do

• Build and develop a high-performing software engineering organisation that reliably delivers customer value.
• Provide the platform and infrastructure required by machine learning and research teams.
• Coach engineers, team leads, and engineering managers while establishing clear leadership expectations and management frameworks.
• Strengthen engineering practices, including planning, code review, testing, continuous deployment, and risk identification in a safety-critical domain.
• Partner with the Heads of Machine Learning and Product and the CTO to translate company priorities into realistic engineering plans.
• Remain technically engaged through architecture, debugging, design reviews, and pairing with engineers.

Requirements

• Strong software engineering background with successful progression into engineering leadership.
• Experience leading through team leads or engineering managers and developing other leaders.
• Technical proficiency with modern software engineering practices, including TDD, pair programming, and continuous deployment.
• Educational background in the physical sciences.
• Experience building software for scientific, industrial, or data-intensive systems.
• Experience working closely with machine learning or data engineering teams.

Culture & Benefits

• Mission-driven work focused on decarbonising heavy industry and delivering measurable cost and carbon impact.
• Equity through company share options.
• Flexible working arrangements agreed with the team.
• 30 days of holiday plus bank holidays.
• Generous pension scheme and an inclusive workplace built around ownership, honesty, adaptability, kindness, and fun.

Hiring process

• Pair programming exercise focused on reasoning, collaboration, testing, learning, and communication.
• System design discussion covering architectural influence, constraints, operational characteristics, and system evolution.
• Management scenarios and an operating-principles discussion covering incidents, priorities, delivery pressure, career development, ownership, ambition, honesty, adaptability, and kindness.