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Le contrat pour ce poste est de type CDI.
Le poste
Descriptif du poste
As a site reliability engineer at Legion, you will be responsible for building the tools, infrastructure, and services to create a secure, highly scalable, and cost-effective AWS/Kubernetes-based cloud platform
You will be working with everything from infrastructure tooling, automation, build and deployment pipelines, monitoring and logging, containerization, and more! Simply put, the SRE team keeps Legion running for our customers
Support Legion’s public cloud platform, utilizing multiple cloud services and containerization
Develop infrastructure automation leveraging Terraform, Chef, Jenkins, and Golang
Create and manage production alerts. Respond to alerts and conduct a root-cause investigation
Develop automated operational runbooks
Support the deployment of Legion’s WFM solution during and off regular office hours
This role involves participation in on-call rotation
Build and operate internal AI agents that reduce SRE toil — incident triage, runbook execution, alert enrichment, capacity and cost analysis — and own their guardrails, rollback, and reliability
Own the platform that lets other engineers build agents safely: sandboxed execution, scoped credentials, tool/MCP integrations, cost controls, and agent observability
Benefits
$0 monthly premium and other flexible medical, dental, and vision plans effective on the first day of employment
401k plan
Unlimited Paid Time Off and Paid Holidays
Parental Leave
Equity
Monthly Wellness Reimbursement
Monthly Lunch on Legion
Profil recherché
Are you passionate about automation, DevOps, public cloud services, Kubernetes, and observability?
5+ years experience with one or more Infrastructure automation (Terraform, Ansible, etc.), CI/CD pipelines (GIT, Jenkins, etc.), and configuration management tools (Ansible, Chef, etc)
5+ years experience with at least one programming language like Go, Python, Bash, Perl
Hands-on experience building agentic AI systems in production — tool integrations, evaluation, and failure handling — beyond use of AI coding assistants
Bachelors or Masters degree in Computer Science/Engineering or related field
12+ years experience in SRE, DevOps, or other SaaS operations
Hands-on experience with one or more Linux/Unix platforms like RedHat/CentOS/Ubuntu/Amazon Linux
3+ years experience with containerized cloud solutions utilizing Docker, Kubernetes, or AWS EKS. Familiarity with HELM charts
3+ years of hands-on experience with managing AWS services and cloud infrastructure in AWS utilizing Terraform. AWS Certification preferred
Track record of introducing AI into an engineering org’s SDLC with measurable results, and the judgment to name where it should not be used
3+ years of experience with observability tools: Splunk, Nagios, Elasticsearch, Kibana, CloudWatch, and Logstash and ways to scale these systems
3+ years of experience in AWS RDS or Aurora MySQL
Demonstrated ability to work with remote teams
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