Site Reliability Engineer

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.