Azure CloudOps Engineer

This is a remote position.

We are looking for a CloudOps Engineer to operate and continuously improve the reliability, security, scalability, observability, and cost efficiency of our Azure-hosted SaaS products. Our products are deployed across development, QA, staging, and production environments, with infrastructure managed through Terraform and CI/CD automated through GitHub Actions.​

This role will work closely with engineering teams to ensure our SaaS platforms and AI-enabled solutions are deployed consistently, monitored effectively, secured properly, and operated reliably in production.

Environment and Technology Context

• Microsoft Azure-hosted SaaS products across dev, QA, staging, and production environments.
• Terraform for infrastructure as code and repeatable environment provisioning.
• GitHub Actions for application and infrastructure CI/CD workflows.
• Azure services including Static Web Apps, Container Apps, PostgreSQL, Storage Accounts, SignalR, Service Bus, Azure AI Foundry, Speech-to-Text services, Azure Arc, and related services.
• AI-enabled product capabilities including STT workloads, LLM integrations, AI service endpoints, quotas, usage monitoring, latency monitoring, and cost controls.

Key Responsibilities

Cloud Infrastructure Operations

• Manage and support Azure cloud infrastructure across dev, QA, staging, and production environments.
• Maintain operational health of Azure services including Static Web Apps, Container Apps, PostgreSQL, Storage Accounts, SignalR, Service Bus, Azure AI Foundry, Azure Arc, and related platform services.
• Ensure cloud resources are provisioned, configured, monitored, maintained, and retired according to company standards.
• Support environment setup for new products, customers, integrations, and internal initiatives.
• Identify and resolve infrastructure issues affecting performance, reliability, availability, or security.

Terraform and Infrastructure as Code

• Build, maintain, and improve Terraform modules and environment configurations.
• Ensure infrastructure changes are version-controlled, peer-reviewed, tested, approved, and repeatable.
• Manage Terraform state, workspaces, variables, secrets integration, and deployment workflows.
• Detect and resolve configuration drift between Terraform and deployed Azure resources.
• Standardize naming conventions, tagging, resource group structure, environment isolation, and module patterns.
• Support scalable provisioning of new SaaS environments using reusable infrastructure templates.

GitHub Actions and CI/CD

• Build, maintain, and troubleshoot GitHub Actions workflows for application and infrastructure deployments.
• Support CI/CD pipelines for multiple SaaS products and environments.
• Implement deployment promotion flows from development to QA to staging to production.
• Add deployment safeguards such as environment protection rules, approvals, rollback procedures, validation checks, release gates, and audit trails.
• Manage pipeline secrets, service principals, managed identities, and secure deployment credentials.
• Improve build and deployment reliability, speed, traceability, and auditability.

AI Service Operations

• Operate and monitor Azure AI services, including Azure AI Foundry and Speech-to-Text workloads.
• Support production operations for LLM-based integrations and AI-enabled product features.
• Monitor AI service availability, latency, quota usage, token consumption, API failures, throttling, and cost.
• Help define operational standards for AI workloads, including access control, logging, alerting, failover, usage governance, and provider disruption handling.
• Work with engineering teams to troubleshoot AI service issues, integration failures, degraded model responses, or provider-side service disruptions.
• Support secure handling of AI-related secrets, endpoints, keys, managed identities, and private network access where applicable.

Monitoring, Alerting, and Observability

• Implement and maintain monitoring using Azure Monitor, Log Analytics, Application Insights, and related tools.
• Create dashboards for infrastructure, application, database, messaging, storage, AI service, and deployment health.
• Configure alerts for availability, latency, errors, resource saturation, queue depth, failed jobs, failed deployments, database health, quota exhaustion, and cost anomalies.
• Improve signal quality by reducing alert noise and ensuring alerts are actionable.
• Partner with engineering teams to define service-level indicators, service-level objectives, and production health metrics.

Incident Response and Production Support

• Participate in production incident response for cloud infrastructure, deployments, integrations, and platform services.
• Triage and resolve issues across Azure services, CI/CD pipelines, Terraform, networking, databases, messaging, and AI integrations.
• Create and maintain runbooks for common operational issues.
• Support root cause analysis and post-incident reviews.
• Implement preventive actions after incidents to improve system reliability.
• Help define severity levels, escalation paths, response expectations, on-call processes, and production support procedures.

Security, Identity, and Access Management

• Implement cloud security best practices across Azure environments.
• Manage Azure RBAC, managed identities, service principals, Key Vault access, and least-privilege permissions.
• Secure GitHub Actions workflows, deployment credentials, environment secrets, and production access.
• Support secret rotation, certificate management, and secure configuration management.
• Help enforce network security using private endpoints, firewalls, IP restrictions, and environment-specific access rules.
• Support compliance readiness for audits, security reviews, customer due diligence, SOC 2, ISO 27001, or similar frameworks.

Database, Storage, and Messaging Operations

• Support operational management of Azure PostgreSQL databases, including backups, restores, performance monitoring, connection limits, high availability, and capacity planning.
• Monitor and maintain Azure Storage Accounts, lifecycle policies, access controls, backup strategy, and usage trends.
• Support Azure Service Bus operations, including queue/topic monitoring, dead-letter handling, retry behavior, and throughput issues.
• Support SignalR operational health, connection metrics, scaling behavior, and related production issues.

Cost Management and Optimization

• Monitor Azure spend across products, environments, services, and customers where applicable.
• Implement tagging standards to support cost allocation by product, environment, customer, or business unit.
• Create cost dashboards, budget alerts, anomaly detection processes, and recurring cost reviews.
• Identify underutilized resources and recommend right-sizing opportunities.
• Review AI service costs, LLM usage, token consumption, STT usage, storage growth, database sizing, and environment costs.
• Recommend savings plans, reservations, scaling rules, lifecycle policies, or shutdown schedules where appropriate.

Reliability, Backup, and Disaster Recovery

• Define and maintain backup and recovery procedures for critical cloud services.
• Test database restores and validate backup reliability.
• Help define recovery time objectives and recovery point objectives for production systems.
• Support disaster recovery planning for SaaS products and customer-facing services.
• Improve resilience through scaling rules, failover patterns, health checks, synthetic monitoring, and production readiness reviews.

Documentation and Operational Standards

• Create and maintain CloudOps documentation, runbooks, deployment guides, troubleshooting guides, and environment standards.
• Define standards for resource naming, tagging, logging, alerting, access control, Terraform structure, GitHub Actions workflow patterns, and production changes.
• Document operational procedures for cloud services, CI/CD workflows, AI services, and incident response.
• Enable engineering teams with reusable patterns, templates, and self-service guidance.

Requirements

Required Qualifications

• 7+ years of hands-on experience operating production workloads in Microsoft Azure.
• Strong experience with Terraform and infrastructure as code.
• Experience building and maintaining CI/CD pipelines using GitHub Actions.
• Experience supporting containerized workloads, preferably Azure Container Apps or similar platforms.
• Experience with Azure monitoring and observability tools such as Azure Monitor, Log Analytics, and Application Insights.
• Experience with Azure PostgreSQL or similar managed relational databases.
• Strong understanding of Azure networking, DNS, identity, RBAC, managed identities, Key Vault, and security best practices.
• Experience troubleshooting production incidents across infrastructure, application deployments, networking, and cloud services.
• Comfortable writing scripts using Bash, PowerShell, Python, or similar tools.
• Strong documentation, communication, and cross-functional collaboration skills.

Preferred Qualifications

• Experience operating AI-enabled applications or Azure AI services.
• Experience with Azure AI Foundry, Azure OpenAI, Speech-to-Text, or LLM-based integrations.
• Experience monitoring AI service usage, quotas, latency, throttling, token consumption, and cost.
• Experience with Azure Service Bus, SignalR, Storage Accounts, and Static Web Apps.
• Experience with Azure Arc.
• Experience supporting multi-product or multi-tenant SaaS platforms.
• Experience with SOC 2, ISO 27001, or similar compliance frameworks.
• Experience with FinOps, cloud cost governance, or Azure cost optimization.
• Experience designing production support processes, incident response workflows, on-call rotations, and operational runbooks.

Benefits

• Competitive salary commensurate with experience.
• Opportunities for career advancement and professional development.
• Experience collaborating with a diverse, global team within a remote work setting.

Originally posted on Himalayas