Site Reliability Engineer - JL6

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Infosys in Bengaluru seeks an experienced Site Reliability Engineer to design and manage scalable services from conception to deployment across global clouds. You will implement robust architectures, optimize performance, and drive automation to improve reliability.

You will develop AI/ML driven monitoring, integrate GenAI and AIOps platforms, and push proactive remediation to minimize downtime and operational toil.

Qualifications

• Bachelor of Engineering required.
• Experience with DevOps/SRE practices.
• Proficiency in one or more programming languages such as Python, Ruby, or Go and understanding of Object Oriented Programming.

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 across clouds worldwide.
• Define and implement standards and best practices related to system architecture, deployment, metrics, and operational tasks.
• Support services through monitoring availability, system health, and incident response.
• Improve system performance, delivery, and efficiency through automation, process refinement, and postmortem reviews.
• Engage in communications across all areas of the organization.
• Troubleshooting and monitoring production systems to ensure the highest uptimes.
• Support and improve high-availability architectures and manage operational activity.
• Integrate GenAI and AIOps tools to automate incident detection, root cause analysis, and resolution workflows.
• Apply Prompt Engineering to enhance AI interactions with observability and automation platforms.
• Leverage cloud AI capabilities to architect intelligent SRE solutions.
• Design, implement, and maintain AI/ML driven monitoring and alerting systems.
• Develop and train ML models using operational telemetry for predictive analytics and intelligent automation.
• Evaluate and deploy AIOps platforms to enhance observability and reduce noise.

Education

Bachelor of Engineering

Tools

AWS Bedrock

Azure OpenAI

GCP Vertex AI

Job description

Roles & ResponsibilitiesRoles 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.
  Educational RequirementBachelor of Engineering
  Preferred SkillsTechnology->DevOps->Site Reliability Engineering(SRE)
  Service LineQuality