Senior Engineer II - SRE (AI-First)

LinuxCareers; Chennai; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Contentstack is seeking a Senior Engineer II - SRE (AI-First) to ensure reliability of a multi-tenant SaaS platform. You will own SLOs/SLIs, manage on-call incidents, and lead AI-assisted deployment and incident response workflows. The role emphasizes Kubernetes operations, Helm charts, and scalable CI/CD pipelines.

You will design and automate workflows with Argo CD, Terraform, and observability tools like Datadog while mentoring engineers and coordinating with SecOps on cluster upgrades.

Qualifications

• Proven production on-call ownership and incident command experience for SaaS platforms with documented postmortems.
• Hands-on experience defining and operating SLIs, SLOs, and error budgets for real services in production.
• Deep day-2 production Kubernetes operation and troubleshooting experience with EKS, including scheduling, autoscaling, resource management, and add-ons.

Responsibilities

• Define, instrument, and operate SLIs, SLOs, and error budgets for platform services; drive follow-through when budgets are at risk.
• Hold primary on-call responsibility, act as incident commander, run blameless postmortems, and use AI-assisted analysis to improve triage, root-cause identification, and MTTR.
• Design, operate, and optimize CI/CD pipelines including caching, parallel execution, automated testing, security scanning, and deployment verification using Artifactory.
• Implement and operate GitOps with Argo CD including canary and blue/green rollouts, automated validation, and rollback capabilities.
• Build and maintain production-grade Helm charts and libraries with testing, versioning, policy validation, and reusable standards; operate Kubernetes day-2 operations at scale.
• Identify and eliminate recurring operational work through automation in Python, Bash, and Ansible; define AI guardrails and review processes for AI-generated deployment and pipeline code.
• Contribute to design and architecture reviews, mentor engineers, and partner cross-team with Infrastructure SecOps on Terraform changes and cluster upgrades.

Skills

SLIs/SLOs

Incident Command

Kubernetes

Helm charts

GitOps Argo CD

CI/CD pipelines

Python

Bash

Ansible

Terraform

AI-assisted workflows

Observability Datadog

On-call ownership

Tools

Argo CD

Flux

Artifactory

Helm

Terraform

Datadog

Job description

Contentstack is an Agentic Experience Platform company redefining how digital experiences are built and managed. This Senior Engineer II - SRE (AI-First) role focuses on ensuring reliability of a multi-tenant SaaS platform through SLO/SLI ownership, progressive delivery, release management, and Kubernetes operations while integrating AI-assisted workflows into deployment and incident response processes.

What You’ll Do

• Define, instrument, and operate SLIs, SLOs, and error budgets for platform services; drive follow-through when budgets are at risk
• Hold primary on-call responsibility, act as incident commander, run blameless postmortems, and use AI-assisted analysis to improve triage, root-cause identification, and MTTR
• Design, operate, and optimize CI/CD pipelines including caching, parallel execution, automated testing, security scanning, and deployment verification using Artifactory
• Implement and operate GitOps with Argo CD including canary and blue/green rollouts, automated validation, and rollback capabilities
• Build and maintain production-grade Helm charts and libraries with testing, versioning, policy validation, and reusable standards; operate Kubernetes day-2 operations at scale
• Identify and eliminate recurring operational work through automation in Python, Bash, and Ansible; define AI guardrails and review processes for AI-generated deployment and pipeline code
• Contribute to design and architecture reviews, mentor engineers, and partner cross-team with Infrastructure SecOps on Terraform changes and cluster upgrades

What You Need

• Proven production on-call ownership and incident command experience for SaaS platforms with documented postmortems
• Hands-on experience defining and operating SLIs, SLOs, and error budgets for real services in production
• Deep day-2 production Kubernetes operation and troubleshooting experience with EKS, including scheduling, autoscaling, resource management, and add-ons
• Demonstrated expertise writing and maintaining Helm charts and libraries that other teams depend on, with tests and CI integration
• Proven CI/CD pipeline ownership at scale with practical experience in progressive delivery tools such as Argo CD, Flux, or equivalent
• Strong Linux fundamentals, load balancing knowledge, and application clustering expertise with ability to debug using logs, stack traces, and core dumps
• Hands-on observability experience building monitors and dashboards in Datadog or equivalent tools
• Demonstrated AI-assisted workflow experience: built an agent, MCP integration, prompt/context library, or AI-assisted review/incident workflow with documented rationale for where not to use AI

Nice to Have

• Experience with multiple progressive delivery frameworks or release engineering patterns beyond Argo CD
• Familiarity with security scanning and artifact management best practices
• Prior experience in multi-tenant platform reliability engineering