DevOps / SRE / AIOps Engineer – Google Cloud

JUTEQ is an AI-native and cloud-native technology consulting firm helping enterprises in financial services, telecom, and healthcare build intelligent, production-grade systems. We combine the power of GenAI, cloud architecture, and automation to deliver next-generation business tools.

We’re seeking a DevOps/Site Reliability Engineer (SRE) with experience in Google Cloud Platform (GCP) to lead and evolve our AI infrastructure as we scale multi-tenant agentic systems across automotive and enterprise use cases. This is a hands-on role working at the intersection of automation, observability, and production AI system reliability.

What You’ll Work On

Platform Reliability & Automation

• Own deployment pipelines, autoscaling, and high-availability for AI microservices running on GCP (Cloud Run, GKE, App Engine)
• Design and optimize CI/CD pipelines using Cloud Build, Skaffold, GitHub Actions
• Implement intelligent autoscaling strategies based on LLM cost, latency, and throughput
• Use Infrastructure as Code (Terraform, Deployment Manager) for repeatable cloud provisioning

Monitoring & Observability

• Deploy monitoring and alerting across Cloud Logging, Cloud Monitoring, and custom dashboards for agent performance metrics
• Define SLOs and SLIs for key services; implement failover and rollback strategies
• Build observability into agent workflows: latency, success rate, AI token consumption, prompt drift, etc.

Data & AI Infrastructure

• Manage access, scaling, and resilience of data services: BigQuery, Firestore, Memorystore, Cloud Storage, Pub/Sub
• Support model integration workflows with Vertex AI and third-party LLM providers (OpenAI, Anthropic, etc.)
• Monitor and secure retrieval pipelines (RAG, embedding generation, vector DBs)

Security & Compliance

• Implement and maintain IAM policies, workload identity, and service-to-service authentication
• Lead incident response and postmortem analysis for production outages
• Ensure systems comply with data residency, privacy, and SOC2/GDPR requirements

What We’re Looking For

Experience & Skills

• 4+ years of DevOps or SRE experience, with at least 2+ years on GCP
• Strong understanding of GCP products including Cloud Run, GKE, Cloud Build, BigQuery, Pub/Sub, Cloud Monitoring
• Experience with CI/CD and GitOps workflows (GitHub Actions, ArgoCD, etc.) and Observability/Monitoring
• Deep knowledge of containerization, Docker, and Kubernetes
• Familiarity with AI infrastructure (LLMs, prompt evaluation, LangChain/CrewAI patterns) is a strong plus
• Experience with alerting and logging using Prometheus, Grafana, or GCP-native tools
• Proficient in scripting (Python, Bash, Go preferred)

Bonus Points

• Experience managing infrastructure for AI agent systems or GenAI workloads
• Familiarity with multi-tenant SaaS platforms
• Understanding of RAG pipelines, embedding generation, or agent orchestration
• Certifications: Google Professional Cloud DevOps Engineer or equivalent

Why Join Us

• Shape the infrastructure behind real-world AI agents used by automotive dealerships and enterprises
• Work alongside AI developers, product engineers, and solution architects
• Ship fast in a zero-to-one environment while building for scale
• Own platform-level impact across reliability, security, cost, and developer productivity

How to Apply

Please send:

• Your resume highlighting DevOps/SRE experience on GCP
• GitHub or portfolio links showcasing infrastructure projects or CI/CD pipelines
• (Optional) A short Loom or video describing your favorite system you’ve built or scaled