Senior Site Reliability Engineer, Algolia
AI Platform
€66.8-96.9k
AI search solutions
Be an early applicant
AI search solutions
501-1000 employees
Be an early applicant
€66.8-96.9k
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
- Strong hands-on production experience with at least one major cloud provider: GCP, AWS or Azure
- Strong experience designing and operating Kubernetes and cloud-native production systems at scale
- Strong understanding of distributed systems, networking and reliability engineering
- Experience operating business-critical systems with strong availability, scalability and operational requirements
- Ability to independently own ambiguous, cross-team technical problems and drive them to measurable outcomes
- Strong automation mindset and ability to balance reliability, engineering velocity and cost
- Excellent written and spoken English
Desirable
- Go and/or Python engineering experience
- Experience with infrastructure supporting AI/ML workloads, model serving, GPUs or other compute-intensive systems
- Comfortable working AI-first, using coding agents, agentic development workflows, AI-assisted debugging and automation 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 Senior Site Reliability Engineer who can independently own complex production systems, drive technical decisions across teams, and help shape reliable and efficient infrastructure at scale
- Own and evolve production infrastructure supporting AI-related workloads and services at scale
- Design and operate highly available Kubernetes-based platforms
- Drive reliability through SLOs, observability, capacity planning and production guardrails
- Lead complex production investigations and turn findings into durable architectural improvements
- Improve shared infrastructure across networking, databases, service communication and compute
- Build better CI/CD, progressive delivery, automation and developer experience
- Drive cloud infrastructure efficiency and FinOps initiatives
- Participate in and improve on-call and incident response
- Mentor engineers and raise the technical bar for reliability and production engineering
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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