Engineering Site Lead

Perplexity is revolutionizing how people discover and interact with information through AI-powered search and knowledge tools. As we expand our global footprint, we're establishing a strategic presence in London to drive innovation and growth across Europe.

The Role:

We're seeking an exceptional Site Lead to establish and scale our London office. This is a unique opportunity to shape Perplexity's presence in one of the world's leading tech hubs, building teams and culture from the ground up while driving technical excellence in infrastructure and AI systems.

As Site Lead, you'll serve as the face of Perplexity in London, responsible for building our technical organization, fostering a world-class engineering culture, and directly managing one or more infrastructure teams. You'll report to senior leadership and work cross-functionally with teams across our global footprint.

The individual in this role will manage teams in LON themselves while also facilitating.

Responsibilities:

Site Leadership & Culture

• Establish and lead Perplexity's London office, setting the cultural foundation and operating principles

• Build a collaborative, high-performance engineering culture that aligns with Perplexity's values while embracing the strengths of the London tech ecosystem

• Serve as the primary point of contact for all London-based activities and represent the site in company-wide strategic discussions

• Partner with People/HR, Finance, and Operations to ensure seamless site operations

• Drive local community engagement, partnerships, and Perplexity's brand presence in the London and European tech community

Technical Leadership:

• Directly manage and mentor one or more infrastructure or AI infrastructure teams in London (5-15+ engineers)

• Set technical direction and strategy for London-based infrastructure initiatives in alignment with company-wide goals

• Drive architectural decisions and technical excellence across teams

• Ensure robust systems for deployment, monitoring, scalability, and reliability of infrastructure supporting AI/ML workloads

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