Builds and maintains scalable infrastructure for real-time analytics and ML workloads, focusing on reliability, automation, CI/CD, monitoring, and incident response. Requires 8+ years SRE/DevOps experience with Kubernetes, Terraform, Linux, and observability tools.
210k – 240k
On-site8+ YOEDevOps / SRE
About the role
Key Responsibilities
Design, build, and maintain scalable infrastructure to support real-time analytics and machine learning workloads
Improve system reliability and performance through automation, observability, and proactive capacity planning
Own and evolve CI/CD pipelines, deployment automation, rollback mechanisms, and config management
Implement and maintain monitoring, alerting, and incident response processes (SLOs, runbooks, on-call rotations)
Collaborate across engineering and data science teams to drive a culture of performance and reliability
Ensure security, compliance, and operational readiness across our cloud infrastructure
Drive post-incident analysis and continuous improvement initiatives
What Will Help You Succeed
8+ years of experience in SRE, DevOps, or infrastructure engineering roles
5+ years of experience with datacenter operations and/or system and network administration
Experience with containerization (Docker), and orchestration (Kubernetes)
Strong knowledge of Linux systems, networking, and systems performance tuning
Solid understanding of infrastructure-as-code (e.g., Terraform, Ansible)
Good programming skills and ability to apply sound coding principles to IaC and scripting code with languages such as Terraform, Ansible, Bash (shell scripting), and/or Python
Experience with monitoring and observability stacks (e.g., Prometheus, Grafana, Datadog, ELK, OpenTelemetry)
Proficiency with CI/CD tools and pipelines (e.g., GitHub Actions, ArgoCD, etc.)
Ability to debug complex systems and automate solutions in scripting languages
Excellent communication skills and the ability to work cross-functionally
Nice-to-Have
Experience with cloud and managed services (e.g. AWS)
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