Architect

Virtusa; Gurugram District; Sur place; INR 3 000 000 - 4 200 000; Plein temps

Résumé du poste

Virtusa is looking for a Site Reliability Engineer/Lead to advance observability, reliability, and performance across applications and infrastructure in Gurugram. You will design Datadog solutions, implement SLOs, and drive incident response improvements with automation and CI/CD practices.

You will collaborate with application, platform, and operations teams to onboard services, reduce noise, and deliver production-ready systems using Pulumi and AI-assisted tooling.

Qualifications

• Strong experience in Datadog, observability, monitoring, alerting, incident response, and automation.
• Hands-on, automation-focused with collaboration across application, infra, cloud, and operations teams.

Responsabilités

• Design, build, and maintain observability solutions using Datadog across apps, infra, cloud, and services.
• Implement and manage metrics, logs, traces, APM, RUM, dashboards, monitors, SLOs, and service catalog capabilities.
• Build effective alerting strategies to reduce noise and improve signal quality.
• Create and maintain Datadog dashboards for health, performance, critical services, and executive reporting.
• Support incident response by improving detection, triage, escalation, and RCA workflows.
• Onboard new applications into Datadog observability standards.
• Review monitors and alerts to improve thresholds, routing, ownership, and prioritization.
• Integrate Datadog with enterprise tools like Freshservice, Slack, Teams, Jira, GitHub, AWS, and Fastly.
• Automate observability deployment, configuration, and onboarding patterns using Pulumi and CI/CD.
• Improve instrumentation for logs, metrics, traces, and APM with engineering teams.
• Leverage AI tools to boost productivity and troubleshooting in observability tasks.
• Build runbooks, dashboards, and troubleshooting guides for production support.
• Participate in production readiness reviews, incident reviews, and post-incident improvements.

Connaissances

Automation

Observability

Incident response

SRE practices

Team collaboration

Outils

Datadog

Pulumi

CI/CD

Freshservice

Slack

Microsoft Teams

Jira

GitHub

AWS

Fastly

Description du poste

About The Role

We are looking for a Site Reliability Engineer/Lead with strong experience in Datadog, observability, monitoring, alerting, incident response, and automation. This role will help improve the reliability, availability, and performance of our applications and infrastructure by building scalable monitoring solutions, reducing operational noise, improving alert quality, and supporting production readiness across teams.

The ideal candidate is hands-on, automation-focused, and comfortable working with application, infrastructure, cloud, and operations teams to drive better reliability outcomes.

Key Responsibilities

• Design, build, and maintain observability solutions using Datadog across applications, infrastructure, cloud platforms, and services.


• Implement and manage metrics, logs, traces, APM, RUM, synthetics, dashboards, monitors, SLOs, and service catalog capabilities.


• Build effective alerting strategies that reduce noise, prevent alert storms, and improve signal quality.


• Create and maintain Datadog dashboards for application health, infrastructure performance, business-critical services, and executive-level reporting.


• Support incident response by improving detection, triage, escalation, and root cause analysis workflows.


• Partner with application and platform teams to define meaningful SLIs, SLOs, and error budgets.


• Help onboard new applications and services into Datadog observability standards.


• Review existing monitors and alerts to improve thresholds, routing, ownership, and priority mapping.


• Support integration of Datadog with enterprise tools and platforms such as Freshservice, Slack, Microsoft Teams, Jira, GitHub, AWS, and Fastly.


• Automate observability deployment, configuration, and repeatable onboarding patterns using Pulumi and CI/CD practices.


• Work with engineering teams to improve instrumentation for logs, metrics, traces, and application performance monitoring.


• Use AI-assisted engineering tools such as Cursor, Claude, or similar AI coding assistants to improve productivity, accelerate troubleshooting, support automation, and assist with observability engineering tasks.


• Build runbooks, operational dashboards, and troubleshooting guides for production support teams.


• Participate in production readiness reviews, incident reviews, and post-incident improvement planning.