Site Reliability Engineer; AI Acceleration- Hybrid
Listed on 2026-07-10
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IT/Tech
Cloud Computing: Infrastructure & Operations, Systems Engineer, SRE/Site Reliability, IT Infrastructure
Work Authorization:
Must be authorized to work in the U.S. without current or future sponsorship
You will be a core member of the SRE team, responsible for the reliability, automation, and observability of the infrastructure that the company runs on. You will work across colocation, on-premises lab environments, and cloud platforms — and you will own your systems end-to-end, from initial provisioning through live incident response.
You will partner with hardware and software development teams to support their workload needs, including CI/CD pipelines and automation layer and the associated CI/CD pipelines and automation layer for software tooling. You will also support customer-facing environments where partners collaborate on hardware and software deployments.
What You Will Do Infrastructure Operations- Own reliability and availability of assigned infrastructure domains: colo server fleets, on-premises lab clusters, cloud environments (AWS, Azure, GCP), and customer-facing platform services.
- Perform hands-on infrastructure work: server provisioning, OS configuration, network setup, storage management, and hardware troubleshooting from bare metal up.
- Conduct capacity planning and hardware lifecycle management for assigned infrastructure domains; track and report cloud spend for your domains to support Fin Ops and workload placement decisions.
- Own IaC and configuration management (Terraform, Ansible) for your infrastructure domains — all provisioning and changes through code, not manual steps.
- Build, deploy and document automation to eliminate toil: host lifecycle management, fleet health checks, auto-remediation workflows, and self-service tooling for engineering teams.
- Develop networking automations for cluster interconnects, VLAN management, and lab network configurations.
- Contribute to shared IaC modules and automation libraries used across the global SRE and data center services teams.
- Design and maintain monitoring dashboards, alerting, and SLIs (Prometheus/Grafana, Data Dog) for your infrastructure domains — ensuring signal quality, actionable alerts, and contributing to AIOps-driven detection workflows that reduce time to detect and respond.
- Participate in on-call rotation; triage and resolve incidents from bare metal to application layer using structured, AI-assisted workflows — distinguishing infrastructure faults from software or hardware product issues and escalating with clear context.
- Produce high-quality RCA reports for P0/P1 incidents with root cause analysis and tracked action items.
- Detect performance issues, recommend solutions, and implement fixes that permanently improve system reliability.
- Support and operate platform services used by both internal teams and external customers for hardware and software deployment collaboration with d-Matrix.
- Ensure QoS and uptime commitments for customer-facing environments; elevate reliability risks proactively.
- Document platform configurations, access procedures, and operational runbooks for customer environments.
- Maintain high-quality runbooks, architecture diagrams, and troubleshooting guides — documentation is part of the job, not an afterthought.
- Partner with the Dev Ops team to ensure infrastructure reliability supports CI/CD pipeline performance and developer experience.
- Serve as a technical resource for engineering teams — sharing operational knowledge and raising infrastructure risks early.
- Bachelor's or Master's in Computer Science, Electrical Engineering, or related field (or equivalent experience); 5+ years in SRE, infrastructure engineering, or systems administration.
- Strong Linux systems knowledge: networking, storage, systemd, package management, kernel parameters, and performance diagnostics.
- Hands-on experience with colocation or on-premises server infrastructure — physical hardware, rack networking, and bare-metal provisioning.
- Hands-on experience deploying and operating AI-driven infrastructure tools — AIOps platforms, intelligent alerting, anomaly detection, or LLM-assisted diagnostics — in production…
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