Site Reliability Engineer (GCP SRE) - AI
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Job description
We are seeking an experienced Google Cloud Site Reliability Engineer (GCP SRE) with expertise in Google Cloud Platform (GCP), Site Reliability Engineering, Kubernetes, and AI/ML platforms. The ideal candidate will be responsible for ensuring the reliability, scalability, availability, and operational excellence of cloud-native applications while supporting Vertex AI, Agentic AI solutions, and large-scale production environments. The candidate should have strong experience in incident management, production support, cloud monitoring, and Kubernetes-based deployments, with the ability to reduce operational noise through proactive observability and automation. Key Responsibilities
- Design, deploy, and support highly available applications on Google Cloud Platform (GCP).
- Maintain production reliability and uptime following SRE principles.
- Monitor cloud infrastructure and applications using observability tools.
- Lead P1/P2 incident management, root cause analysis (RCA), and post-incident reviews.
- Implement automation to reduce operational overhead and monitoring noise.
- Deploy and manage Kubernetes workloads on Google Kubernetes Engine (GKE).
- Build and maintain CI/CD pipelines for cloud-native applications.
- Support Vertex AI model training, deployment, and inference pipelines.
- Collaborate with AI/ML engineers to operationalize machine learning solutions.
- Work with Agentic AI assistants and AI-driven automation workflows.
- Optimize cloud infrastructure performance, scalability, and cost.
- Implement security, governance, and best practices across GCP environments.
- Participate in on-call support and production incident rotations.
Required Technical Skills Google Cloud Platform
- Google Cloud Platform (GCP)
- Google Kubernetes Engine (GKE)
- Pub/Sub
- BigQuery
- Cloud Spanner
- Dataflow
- Firestore
- Vertex AI
Site Reliability Engineering
- Site Reliability Engineering (SRE)
- Production Support
- Incident Management
- Root Cause Analysis (RCA)
- High Availability
- Disaster Recovery
- Performance Monitoring
- Reliability Engineering
Containers & DevOps
- Kubernetes
- Docker
- Helm
- CI/CD
- Git
- Jenkins / GitHub Actions (Preferred)
AI / ML
- Vertex AI
- Machine Learning Pipelines
- Model Deployment
- Agentic AI
- AI Assistants
- LLM Operations (Preferred)
Monitoring & Observability
- Prometheus
- Grafana
- Cloud Monitoring
- Cloud Logging
- Alerting
- Monitoring Optimization
Programming
- Python
- Bash/Shell Scripting
- YAML
Preferred Skills
- AWS (EC2, S3, Lambda)
- Terraform
- Infrastructure as Code (IaC)
- Anthos
- Service Mesh (Istio)
- GitOps
- ArgoCD
- AI/ML Operations (MLOps)
- DevSecOps, * Google Cloud Platform (GCP)
- Kubernetes (GKE)
- Docker
- Helm
- Pub/Sub
- BigQuery
- Cloud Spanner
- Dataflow
- Firestore
- Vertex AI
- Incident Management
- Site Reliability Engineering (SRE)
- Monitoring & Observability
- Root Cause Analysis (RCA)
- Agentic AI
- AI Assistants
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
- 6-8 years of experience in Site Reliability Engineering or Cloud Operations.
- Strong hands-on experience with Google Cloud Platform.
- Excellent troubleshooting, communication, and production support skills.
About the company
Bright Vision Technologies
- Cumming, GA
-
$100,000-150,000 per year Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations…
- 1 day ago
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