Job Summary

We are seeking a skilled and forward-thinking CloudOps Engineer to join our Cloud Operations team. In this role, you will be responsible for maintaining, optimizing, and scaling our contemporary SaaS-based eCommerce infrastructure. In addition to core cloud operations, you will play a key role in supporting our next-generation AI features, LLM orchestration pipelines, and agentic commerce workflows, ensuring high availability, security, and peak performance.

Key Responsibilities

- Cloud Infrastructure: Deploy, configure, and maintain scalable, cloud-based solutions on Google Cloud Platform (GCP).
- Resource Cost Optimization: Monitor and optimize cloud resources including compute, memory, and database workloads to maximize performance and drive cost efficiency (e.g., managing Committed Use Discounts).
- Container Orchestration: Troubleshoot Kubernetes (GKE) workloads, manage container networking, optimize autoscaling policies, and implement best practices for containerized applications.
- AI Data Infrastructure Support: Provision and manage infrastructure optimized for AI workloads, including vector databases, model deployment pipelines, and API gateways for LLM orchestration.
- Observability: Configure and manage Google Cloud Monitoring, Logging, and Alerting (OpsSuite) to ensure proactive detection of system anomalies and AI inference latency issues.
- Security Networking: Implement and enforce strict IAM policies, secure VPC networking, and firewall rules to protect sensitive enterprise and AI-training data assets.





Qualifications and Skills

Education Experience

- Bachelor s degree in Computer Science, Engineering, or a related technical field.
- 1 to 2 years of professional experience in CloudOps, DevOps, or Site Reliability Engineering (SRE).

Core Technical Skills

- Cloud Platform: Hands-on experience with core Google Cloud Platform (GCP) services (Compute Engine, GKE, Cloud Storage, Cloud SQL, VPC).
- Containers Orchestration: Expertise in Docker containerization and Kubernetes management.
- Infrastructure as Code: Solid foundational experience with Terraform or similar IaC tools for reproducible deployments.
- Systems OS: Proficiency in managing, configuring, and troubleshooting Linux systems, particularly Ubuntu and Rocky Linux.

AI Emerging Tech Requirements (Must-Have)

- AI Infrastructure Familiarity: Understanding of cloud infrastructure requirements for hosting AI models, utilizing vector databases (e.g., Pinecone, Milvus, or pgvector), or managing embedding generation pipelines.
- AI-Driven Workflows: Experience leveraging AI coding assistants (e.g., Claude, GitHub Copilot) to accelerate scripting, debugging, and infrastructure automation tasks.
- API Integration Concepts: Solid understanding of RESTful APIs, JSON payloads

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 CloudOps Engineer (Mysuru)
🏢 unilog
📍 Mysuru