Engineering Site Lead

Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world’s leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world’s most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision‑making for people and assistive AI wherever decisions are being made.

Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that’s growing rapidly for one simple reason: everyone can be curious.

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.

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.

• 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

• 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
• Collaborate with engineering leaders globally to align on technical standards, best practices, and cross‑site initiatives

• Build and scale high‑performing infrastructure and AI infrastructure teams through strategic hiring
• Develop and execute talent acquisition strategy for the London site in partnership with recruiting
• Create career development frameworks and growth opportunities for engineers
• Foster technical mentorship and knowledge sharing across teams and sites

• Partner with Product, Engineering, and Research teams globally to understand infrastructure needs and deliver solutions
• Coordinate with other site leads and engineering leaders to ensure effective cross‑site collaboration
• Contribute to company‑wide infrastructure strategy and roadmap planning
• Facilitate knowledge transfer and best practice sharing across global teams

• 10+ years of experience in software engineering with 5+ years in infrastructure, cloud infrastructure, or AI infrastructure roles
• 3+ years of people management experience, including building and scaling teams
• Proven track record of establishing or significantly growing an engineering site or office
• Deep technical expertise in distributed systems, cloud platforms (AWS, GCP, or Azure), and infrastructure automation
• Experience with infrastructure supporting large‑scale AI/ML systems, including:
  • GPU infrastructure and orchestration
  • ML training and inference pipelines
  • Mo…