Infrastructure Capacity Engineer, Perplexity AI
$225-300k
Equity: In addition to the base salary, equity may be part of the total compensation package.
Office located in Palo Alto, CA
Conversational AI-powered search tool
Be an early applicant
Conversational AI-powered search tool
21-100 employees
Be an early applicant
$225-300k
Equity: In addition to the base salary, equity may be part of the total compensation package.
Office located in Palo Alto, CA
21-100 employees
Company mission
To advance the way people discover and share information.
Role
Who you are
- Minimum of 4+ years of experience in infrastructure capacity planning, systems engineering, or related technical roles at scale
- Proven experience managing infrastructure capacity for high-growth technology companies, preferably with AI/ML workloads or real-time systems
- Strong background in distributed systems architecture, cloud infrastructure (AWS/GCP/Azure), and container orchestration (Kubernetes)
- Experience with capacity modeling tools, forecasting methodologies, and statistical analysis for infrastructure planning
- Proficiency in programming languages such as Python, Go, or similar for automation and tooling development
- Deep understanding of infrastructure monitoring, observability, and performance optimization techniques
- Experience with infrastructure-as-code tools (Terraform, Ansible) and CI/CD pipelines for infrastructure management
- Strong analytical and problem-solving skills with the ability to make data-driven decisions under uncertainty
- Excellent cross-functional collaboration skills and experience working with engineering, product, and business stakeholders
- Experience with large-scale database systems, caching layers, and content delivery networks preferred
- Background in AI/ML infrastructure, LLM inference, GPU cluster management, or high-performance computing is a plus
What the job involves
- Perplexity is seeking an experienced Infrastructure Capacity Engineer to own our infrastructure scaling, capacity planning, and resource optimization across our AI/ML infrastructure. The ideal candidate will have deep experience in large-scale distributed systems, capacity modeling, and infrastructure efficiency optimization to support our rapidly growing AI products and user base
- Design and implement comprehensive capacity planning models and forecasting systems that predict infrastructure needs across compute, storage, and network resources for our AI/ML workloads
- Build and maintain automated capacity management systems that dynamically scale our infrastructure based on real-time demand patterns and usage forecasts
- Lead cross-functional capacity planning initiatives including hardware procurement, data center expansion, and cloud resource optimization
- Develop sophisticated monitoring and alerting systems that provide early warning indicators for capacity constraints and performance degradation
- Create and maintain detailed infrastructure capacity models that account for seasonal patterns, product launches, and scaling efficiency across different workload types
- Optimize resource utilization and cost efficiency through advanced placement algorithms, load balancing strategies, and infrastructure rightsizing
- Design and implement disaster recovery and business continuity plans that ensure service availability during infrastructure failures or capacity emergencies
- Collaborate with Site Reliability Engineering and Platform teams to establish capacity-aware deployment strategies and infrastructure automation
- Play a leading role in defining the capacity engineering discipline within Perplexity’s engineering organization
Our take
As artificial intelligence continues to drive changes in both business operations and day-to-day lives, Perplexity AI delivers an intelligent search engine powered by conversational AI, to improve search outcomes and "unlock the power of knowledge" for all.
Reaching impressive heights of 10 million monthly visits, Perplexity's "ask anything" method of search is clearly a popular one. What sets it apart from other search engines is in its answers, which are concise and fully cited, responding to the user query rather than simply providing a place in which they can scroll to find it themselves.
The company has raised substantial funding, with contributions from former execs at companies like OpenAI, Meta, and Quora, demonstrating the interest that it has drummed up in the space. Having doubled its annual recurring revenue between 2023 and 24, this investment will allow Perplexity AI to continue building out its product, and accelerate growth into the future.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 8 rounds)
Jul 2025
$100m
LATE VC
May 2025
$500m
LATE VC
Total funding: $1.5bn
Company benefits
- Equity
- Comprehensive health, dental, and vision insurance for you and your dependents
- 401(k)
- Generous home-office stipend
Company HQ
Financial District, San Francisco, CA
Leadership
Aravind Srinivas
(Co-Founder & CEO)Former Research Scientist at OpenAI, who has interned in Research at Google and Deep Mind. Obtained a PhD in Computer Science from the University of California, Berkeley.
Denis Yarats
(Co-Founder & CTO)PhD Student in AI at NYU. Former AI Research Scientist at Facebook AI Research, and Staff ML Engineer at Quora.
Johnny Ho
(Co-Founder & CSO)Previously a Quantitative Trader at Tower Research Capital, and Engineer at Quora.
Andy Konwinski
(Co-Founder)Co-Founder and Advisor at Databricks. Co-Founder and General Partner at CS Graduate Ventures, and Instructor at the University of California, Berkeley.
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