Description

Key Exciting Responsibilities 

• Architect, scale, and optimize high-availability cloud infrastructure primarily across Microsoft Azure to ensure seamless enterprise resilience and performance. 
• Build, automate, and streamline scalable Infrastructure as Code (IaC) and continuous delivery pipelines utilizing Terraform, GitHub, and modern CI/CD tooling. 
• Drive observability, incident management, and root cause analysis across complex cloud environments to minimize operational risk and elevate user experience. 
• Modernize platform architecture by supporting automated configuration management, templatizing infrastructure, and moving towards self-service solutions for supporting product development teams.
• Partner closely with security and software engineering teams to champion cloud governance, identity access management, and automated vulnerability mitigation.

Essential Skills & Experience 

• 5+ years of hands-on experience in Site Reliability Engineering, DevOps, or enterprise Cloud Operations. 
• 3+ years of experience architecting and operating enterprise cloud environments (Azure, AWS, or Google Cloud), with a deep understanding of core compute, networking, scalable storage, and disaster recovery principles.
• Demonstrated background in Site Reliability Engineering practices, including defining SLIs/SLOs, implementing enterprise observability (using tools like New Relic, Datadog, OpenTelemetry, etc.), and managing incident response for highly-available cloud products.
• Demonstrated proficiency automating infrastructure and deployments using IaC (Terraform, Bicep, etc.), scripting languages (PowerShell, Bash, etc.), and CI/CD tools such as Azure DevOps, Jenkins, or GitHub. 
• Strong analytical and troubleshooting capability focused on proactive observability and incident resolution.

Bonus Points For 

• Practical experience leveraging modern AI coding assistants (e.g., GitHub Copilot, Cursor, Claude, Gemini) to accelerate infrastructure-as-code development, scripting, and automation.
• Familiarity with AI telemetry and LLMOps tools (such as LangFuse) to monitor agent performance, trace LLM requests, track token spend, and ensure the reliability of AI-powered applications.
• Practical familiarity with container orchestration platforms such as Kubernetes, AKS, or Amazon ECS.
• Experience and working knowledge with SAP BusinessObject BI Platform, and CrystalReport.
• Knowledge of cloud financial operations and resource cost optimization techniques. 
• Background in enterprise cybersecurity governance.
• Experience and working knowledge with event streaming (e.g. Kafka) and modern data platforms (e.g. Databricks, Snowflake)

Key Skills

Education

Any Graduate