Jobs / France / Algolia Limited

Algolia Limited

Site Reliability Engineer, AI Platform

Paris, France Posted 1 month ago

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Skills this job asks for

KubernetesCI/CDNetworkingGoogle CloudAWSAzureEnglishPythonMachine learning

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Sponsorship verdict

No sponsorship evidence yet

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Before you apply

Sponsorship unknown

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About the role

Algolia is the retrieval intelligence layer that turns intent into trusted, decision-grade outcomes. Powering more than 1.7 trillion queries a year for over 18,000 customers with millisecond latency and 99.999% reliability, we are the recognized leader for Search and Product Discovery by top industry analyst firms. The Algolia platform turns a company's products, content, and business rules into data that humans, applications and AI agents can act upon. The result is trusted customer experiences with stronger conversions for measurable business impact. Algolia was built to help users deliver intuitive search experiences across websites and mobile applications. Our Search API serves thousands of customers in more than 100 countries, answering billions of queries every month. Join AI Platform: Powering AI in Production 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. YOU WILL: • 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 YOU MIGHT BE A FIT IF YOU HAVE: • 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 NICE TO HAVE: • 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 Algolia does not discriminate on the basis of race, color, religion, sex, age, national origin, military status, veteran status, disability status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. The annual base salary compensation range for this role reflects market pay data within this location. The exact compensation offered for this role may vary depending on specific location and job-related knowledge, technical skills, and experience; and is

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