Site Reliability Engineer, Algolia
AI Platform
€69.8-96.9k
AI search solutions
Be an early applicant
AI search solutions
501-1000 employees
Be an early applicant
€69.8-96.9k
501-1000 employees
Company mission
To help businesses and developers understand their online users and show them exactly what they need.
Role
Who you are
- Solid hands-on Kubernetes knowledge, including workloads, resource management, and production operations
- Strong experience with Infrastructure as Code, and the lifecycle of cloud infrastructure
- Solid experience building and operating CI/CD pipelines and automated deployment workflows
- Hands-on experience with at least one major cloud provider: GCP, AWS or Azure
- Good understanding of networking, distributed systems and reliability engineering
- Experience with monitoring, observability and troubleshooting production systems
- Strong automation mindset and the ability to take ownership of well-defined production systems and progressively tackle more complex problems
- Excellent written and spoken English
Desirable
- Go and/or Python engineering experience
- Exposure to AI/ML infrastructure and inferences
- Comfortable working AI-first, using coding agents, agentic workflows and AI-assisted debugging to accelerate engineering and operations
What the job involves
- AI Platform builds and operates the shared production foundations supporting Algolia's evolving AI ecosystem
- The team works at the intersection of Site Reliability Engineering, cloud infrastructure, software engineering and AI, helping engineering teams bring AI-powered capabilities to production reliably, securely and efficiently
- Our scope includes Kubernetes, cloud infrastructure, CI/CD, networking, databases, observability, reliability, FinOps and production operations
- We are looking for a Site Reliability Engineer with strong production fundamentals who enjoys solving operational problems, automating repetitive work and progressively taking ownership of complex systems at scale
- Build and operate production infrastructure supporting AI-related workloads and services
- Operate and improve highly available Kubernetes-based platforms
- Improve reliability through SLOs, observability, alerting and capacity management
- Investigate production issues and turn findings into durable fixes and improvements
- Work across networking, databases, compute and service infrastructure
- Improve CI/CD pipelines, deployment automation and developer experience
- Build and maintain infrastructure using Infrastructure as Code
- Participate in on-call, incident response and operational improvements
- Collaborate with experienced engineers across AI Platform and progressively take ownership of broader production areas
Our take
While in-site searching has been available for some time from web search servers such as Google and Bing, its functionality is limited due to it relying on general web scraping techniques which can miss relevant information. By contrast Algolia indexes only the company's site, allowing its search to serve accurate results extremely swiftly, which helps to drive sales conversions aside from making sites far more usable. The efficacy of this solution can be seen from its customer base of over 10,000 companies including the likes of Slack, Zendesk and Lacoste.
To diversify and increase the product range, Algolia have expanded into other real-time APIs such as product recommendations available for eCommerce websites. With the company performing extremely well over the last few years, Algolia have recruited key senior executives to further its growth. As the company continues to scale it seems likely that an IPO is not too distant a prospect.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 7 rounds)
Jul 2021
$150m
SERIES D
Oct 2019
$110m
SERIES C
Total funding: $334m
Company HQ
Barron Park, Palo Alto, CA
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