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 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.
YOU WILL:
- 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
YOU MIGHT BE A FIT IF YOU HAVE:
- 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
