Site Reliability Engineer (GCP SRE) - AI

Purple Drive Technologies LLC
Alpharetta, GA, United States
29 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$135,200.0 - $145,600.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 BigQuery Cloud Computing Computer Programming Continuous Integration DevOps Disaster Recovery Data Flow Control Github
+28 more
Monitoring of Systems Python (Programming Language) Machine Learning Reliability Engineering Prometheus Azure Machine Learning YAML Data Logging Scripting Google Cloud Cloud Monitoring Spring Cloud Istio System Availability Large Language Models Grafana Infrastructure as Code (IaC) Git Kubernetes Information Technology Performance Monitor Machine Learning Operations Virtual Agents Functional Programming Terraform Devsecops Docker Jenkins

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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