Why This Job is Featured on The SaaS Jobs
This Site Reliability Engineer role sits at the core of a high-throughput SaaS platform where availability is part of the product. Supporting Search and Discovery at very large query volumes makes reliability engineering a direct contributor to customer-facing outcomes, not just internal infrastructure. The remit spans operating production services and shaping how reliability is engineered across multiple teams, which is a common pattern in mature SaaS organisations with shared platform needs.
From a SaaS career perspective, the work builds durable expertise in the practices that underpin subscription businesses: measurable service levels, error budgets, incident response automation, and cost-aware scalability. Exposure to Kubernetes, infrastructure as code, and a mixed cloud and bare-metal environment also develops portability across modern SaaS stacks, while the focus on reducing toil reinforces the engineering mindset needed to keep platforms sustainable as usage grows.
The position tends to suit engineers who enjoy operational ownership and improving systems through pragmatic automation rather than one-off fixes. It aligns well with someone who already has some experience running production architectures and wants broader influence through cross-team enablement, clear SLO thinking, and disciplined troubleshooting in a distributed SaaS environment.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Algolia is set to enable every company to create world-class Search and Discovery experiences with an API-first approach. Performance and Scalability is at the heart of our mission: we power 1.5 trillion searches a year, for 10K+ customers all over the world.
If you're a problem solver, able to think outside the box and eager to nurture others and learn from them, then this is your challenge!
The Team
The Fleet team is a Site Reliability Engineering team focusing on one goal: the Search products should always be available. To make this possible, the Fleet team creates pragmatic solutions to optimize the Search products availability and costs at scale, taking into account the needs of customers, the product teams, and the many engineering teams involved in delivering a unique Search Experience to our customers.
The Opportunity
The team is looking for an individual who has a first experience of building and operating scalable architectures. You will contribute to the delivery of solutions that support other engineering teams and will have a direct impact on the success of Algolia's Search products.
In this role, you'll help design and implement systems focused on reliability, scalability, and cost efficiency, while also having opportunities to grow your skills and collaborate with team members.
Your role will include
- Operating the Search products, building self-healing and automated incident response mechanisms
- Building components that improve reliability and performance
- Monitoring and computing the SLO and the error budget of the product you operate
- Reducing the toil and the technical debt by automating tasks and increasing the quality of existing components
- Managing Incidents and Customer Requests
You might be a good fit if you have
- Knowledge of at least one programming language (Python, Golang, Ruby) and you are familiar with software craftsmanship
- Experience working with APIs
- A focus on designing reliable, operable, and highly available applications
- Familiarity with at least Public Cloud Providers like GCP, AWS, or Microsoft Azure, and their Kubernetes service
- A good understanding of Linux system administration, networking, and troubleshooting
- Strong communication and organizational skills
Team’s current stack:
- Programming languages: Golang, Python, Ruby
- CI/CD:Github Actions, CircleCI
- IaC & configuration management:Terraform, Chef
- Platform: Linux, Kubernetes
- Hosting: Bare Metal Servers & Cloud on AWS & Azure
- Monitoring: Datadog & custom monitoring stack for our Search infrastructure
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