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Site Reliability Engineer
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Site Reliability Engineer
InfosysThis job is no longer accepting applications
Job Description
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.
More Info
Key Skills
About Company
Skills:
coreos , Java, Sql, Ubuntu, Git, Docker, Linux, Apache Cassandra, Apache Kafka, Bash, Python, OpenSearch
Skills:
Linux, Software Engineering, Microservices, Java, Windows, Continuous Delivery, Containers, Continuous Integration, Terraform, site reliability concepts, enterprise-authorized AI capabilities, observability, cloud-based infrastructure, AWS Elastic Kubernetes Service
Skills:
Networking, Cloudformation, Firewalls, Routing, AWS CodePipeline, Javascript, Ruby, Azure, Python, AWS, Container Security
Skills:
Software Engineering, Microservices, Java, Continuous Delivery, Windows, Containers, Linux, Continuous Integration, Terraform, cloud-based infrastructure, AI capabilities, site reliability concepts, observability, AWS Elastic Kubernetes Service
Skills:
container , Networking, automation, Dashboards, Grafana, Linux, Datadog, Redis, cloud, Alerts, metrics, traces, infrastructure-as-code, observability data, logs, Cribl, service health views, Flink, ClickHouse, GitOps workflows, OpenTelemetry, BigPanda