Site Reliability Engineer - JL5

Key Responsibilities:

• Roles and Responsibilities
• Design and implement the lifecycle of services from conception to inception including system design build and deployment
• Develop software solutions to enable operability of large scale distributed systems capable of handling millions of transactions and petabytes of data
• Manage capacity and performance to help scale the infrastructure both on public and private clouds around the world
• Define and implement standards and best practices related to System Architecture Deployment metrics operational tasks
• Support services through activities such as monitoring availability system health and incident response
• Improve system performance application delivery and efficiency through automation process refinement postmortem reviews and in depth configuration analysis
• Engage in Communications across all areas of the organization
• Troubleshooting and monitoring production systems to ensure the highest uptimes are maintained
• Support and improve upon existing high availability architecture solutions as well as manage the operational activity
• Integrate Generative AI GenAI and AIOps tools to automate incident detection root cause analysis and resolution workflows e
• g
• self healing scripts intelligent runbooks reducing manual toil and accelerating response times
• Apply Prompt Engineering techniques to enhance interactions with AI based observability and automation platforms improving accuracy and efficiency of AI responses
• Leverage platform specific AI capabilities e
• g
• AWS Bedrock Azure OpenAI GCP Vertex AI to architect intelligent SRE solutions tailored to cloud environments
• Design implement and maintain AI ML driven monitoring and alerting systems to proactively detect anomalies and predict potential failures enabling preemptive remediation
• Develop and train machine learning models using operational telemetry logs metrics events traces to support predictive analytics and intelligent automation
• Evaluate and deploy AIOps platforms e
• g
• Moogsoft Dynatrace Splunk BigPanda Datadog Elastic to enhance observability reduce noise and accelerate incident resolution
• Experience in one or more high level programming languages like Python or Ruby or GoLang and familiar with Object Oriented Programming

Preferred Skills:

Technology->DevOps->DevOps Architecture Consultancy,Technology->AI-Generative AI->Artificial Intelligence - BASIC,Technology->Devops->Ansible