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Salary: EUR 69,768 - 96,900 / annual
Algolia is the retrieval intelligence layer powering over 1.7 trillion queries annually for 18,000+ customers with millisecond latency and 99.999% reliability. The company is the recognized leader in Search and Product Discovery, turning products, content, and business rules into data that humans, applications, and AI agents can act upon.
The AI Platform team builds and operates 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. The scope includes Kubernetes, cloud infrastructure, CI/CD, networking, databases, observability, reliability, FinOps, and production operations.
As a Senior Site Reliability Engineer, you will own and evolve production infrastructure supporting AI-related workloads and services at scale. You will design and operate highly available Kubernetes-based platforms, drive reliability through SLOs, observability, capacity planning, and production guardrails. You will lead complex production investigations and turn findings into durable architectural improvements. Additional responsibilities include improving shared infrastructure across networking, databases, service communication, and compute; building better CI/CD, progressive delivery, automation, and developer experience; driving cloud infrastructure efficiency and FinOps initiatives; participating in and improving on-call and incident response; and mentoring engineers to raise the technical bar for reliability and production engineering.
This is an independent role where you will own ambiguous, cross-team technical problems and drive them to measurable outcomes. You will work in a high-trust environment with emphasis on impact, contribution, and output over physical location, though this position is based in Paris.
REQUIREMENTS:
- 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
