Site Reliability Engineer

Randstad Digital | Torc; United States; Remoto; USD 130.000 - 190.000; Tempo pieno

Descrizione del lavoro

Torc is seeking a Site Reliability Engineer to join the Data & AI Platform Engineering team. You will help keep data and AI platforms reliable, scalable, and secure, working primarily with Google Cloud Platform (GCP) and Kubernetes.

You will contribute to incident response, observability, automation, and reliability improvements across multi-cloud and AI workloads, with a focus on reducing toil and improving deployment readiness.

Competenze

• 6+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, or Infrastructure Engineering.
• Hands-on production experience with GCP, especially GKE, Cloud Run, BigQuery, Pub/Sub, and GCS.
• Experience with Kubernetes/GKE and managing containerized workloads.
• Working experience with Terraform, Helm, or similar Infrastructure-as-Code tools.
• Experience with observability tools and practices, including metrics, logging, tracing, dashboards, and alerting.
• Understanding of SLOs, SLIs, incident management, and production reliability.
• Familiarity with cloud security fundamentals such as IAM, secrets management, encryption, and network policies.
• Proficiency with at least one scripting or systems language such as Python, Bash, or Go.
• Basic experience with CI/CD and GitOps workflows such as GitHub Actions or ArgoCD.
• Strong communication and documentation skills.

Mansioni

• Monitor and support production systems using dashboards, alerts, logs, metrics, and tracing.
• Participate in on-call rotations and respond to production incidents following established processes and runbooks.
• Contribute to post-mortems, root cause analysis, and follow-up improvements.
• Maintain and improve SLOs, SLIs, dashboards, and alerting thresholds.
• Identify repetitive operational tasks and automate them to reduce toil.
• Build and maintain scripts, tooling, and CI/CD components that improve platform reliability.
• Operate workloads across GCP services including GKE, Cloud Run, BigQuery, Pub/Sub, GCS, and Composer.
• Manage infrastructure using Infrastructure-as-Code tools such as Terraform and Helm.
• Support self-service infrastructure initiatives for engineering teams.
• Apply cloud security and governance practices around IAM, encryption, secrets management, network policies, and audit logging.
• Collaborate with engineering teams to incorporate reliability considerations into system design and deployment.

Conoscenze

Strong communication

Documentation

On-call experience

Problem solving

Strumenti

GCP

GKE

Cloud Run

BigQuery

Pub/Sub

GCS

Terraform

Helm

Kubernetes

GitHub Actions

ArgoCD

Descrizione del lavoro

About Torc

Torc is a career-first platform that connects top tech talent with meaningful job opportunities. More than just job matching, Torc is a community — offering events, livestreams, and exclusive content to help professionals grow, learn, and stay connected. When you join Torc, you’re not just finding a job — you’re joining a network that supports your career development every step of the way.

About the Role

We’re looking for a Site Reliability Engineer (SRE) to join a Data & AI Platform Engineering team, helping keep critical data and AI platforms reliable, scalable, secure, and efficient.

In this role, you’ll work with production systems running primarily on Google Cloud Platform (GCP), supporting incident response, observability, infrastructure automation, SLOs, and operational improvements. You’ll also collaborate closely with Data Engineering, AI Platform, and Software Engineering teams and gain exposure to multi-cloud and AI/ML workloads.

This role is ideal for engineers who enjoy solving production reliability challenges, automating repetitive work, and improving how cloud platforms are operated at scale.

What you'll do:

• Monitor and support production systems using dashboards, alerts, logs, metrics, and tracing.
• Participate in on-call rotations and respond to production incidents following established processes and runbooks.
• Contribute to post-mortems, root cause analysis, and follow-up improvements.
• Maintain and improve SLOs, SLIs, dashboards, and alerting thresholds.
• Identify repetitive operational tasks and automate them to reduce toil.
• Build and maintain scripts, tooling, and CI/CD components that improve platform reliability.
• Operate workloads across GCP services including GKE, Cloud Run, BigQuery, Pub/Sub, GCS, and Composer.
• Manage infrastructure using Infrastructure-as-Code tools such as Terraform and Helm.
• Support self-service infrastructure initiatives for engineering teams.
• Apply cloud security and governance practices around IAM, encryption, secrets management, network policies, and audit logging.
• Collaborate with engineering teams to incorporate reliability considerations into system design and deployment.

What we're looking for:

• 6+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, or Infrastructure Engineering.
• Hands-on production experience with GCP, particularly GKE, Cloud Run, BigQuery, Pub/Sub, and GCS.
• Experience with Kubernetes/GKE and managing containerized workloads.
• Working experience with Terraform, Helm, or similar Infrastructure-as-Code tools.
• Experience with observability tools and practices, including metrics, logging, tracing, dashboards, and alerting.
• Understanding of SLOs, SLIs, incident management, and production reliability.
• Familiarity with cloud security fundamentals such as IAM, secrets management, encryption, and network policies.
• Proficiency with at least one scripting or systems language such as Python, Bash, or Go.
• Basic experience with CI/CD and GitOps workflows such as GitHub Actions or ArgoCD.
• Strong communication and documentation skills.

Nice-to-Have:

• Experience with batch or streaming data platforms and pipelines.
• Exposure to Azure or other multi-cloud environments.
• Familiarity with Google SRE practices such as error budgets, toil tracking, and production readiness reviews.
• Experience supporting AI/ML platforms or model-serving infrastructure.
• Exposure to LLM-based or agentic AI workloads.
• Experience with FinOps or cloud cost visibility tooling.
• Experience in retail, e-commerce, or consumer goods environments.

While we may not be able to respond to every applicant, your profile will remain in the Torc Talent Community, giving you access to future opportunities, events, and resources to grow your career.