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# Site Reliability Engineer, AI Platform

- **Company:** Algolia
- **Location:** Paris, France (Remote available)
- **Experience:** Expert
- **Salary:** €69,768.0 - €96,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Engineering, Software Debugging, Distributed Systems, Python (Programming Language), Reliability Engineering, Graphics Processing Unit (GPU), Kubernetes, Machine Learning Operations
- **Published:** September 20, 2026
- **Apply:** https://startup.jobs/senior-site-reliability-engineer-ai-platform-algolia-2-10127594

## About the Role

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., * 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

NICE TO HAVE:

 * 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, * 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

* 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


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