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# Site Reliability Engineer, AI Platform

- **Company:** Algolia
- **Location:** Paris, France (Remote available)
- **Salary:** €69,768.0 - €96,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Software Debugging, Distributed Systems, Python (Programming Language), Reliability Engineering, AI Platforms, Kubernetes, Deployment Automation, Machine Learning Operations
- **Published:** September 19, 2026
- **Apply:** https://startup.jobs/site-reliability-engineer-ai-platform-algolia-2-10127596

## About the Role

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., * 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, * GRIT - Problem-solving and perseverance capability in an ever-changing and growing environment.
 * TRUST - Willingness to trust our co-workers and to take ownership.
 * CANDOR - Ability to receive and give constructive feedback.

## Description

* 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


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