Senior Engineer II - SRE (AI-First)

What is Contentstack?:

Contentstack is redefining how modern digital experiences are built and managed. As the pioneer of the Agentic Experience Platform (AXP), Contentstack brings together structured content and brand governance (Content Cloud), real-time customer data, omnichannel personalization (Data Cloud) and autonomous AI orchestration (Agent OS) into one unified system.

Contentstack helps enterprises move beyond that complexity by connecting content, data and AI in a way that makes digital experiences faster to launch, easier to manage and more adaptive in real time.

Leading brands including Steve Madden, LG Electronics, Subaru of America, Dolce & Gabbana, ASICS, Decathlon, and Caesars Entertainment rely on Contentstack to reduce operational friction and deliver personalized, scalable digital experiences with confidence.

Who Are We?:

At Contentstack we are more than colleagues, we are a tribe. We are global-diverse yet close; distributed yet connected. We do the right thing, even when no one is watching. We care deeply about our customers and the communities we serve.

What you will be working on:

• Reliability of a multi-tenant platform under growth: Defining SLIs and SLOs for the services in your area, instrumenting them honestly, and having the error-budget conversation when one is at risk.
• Making releases boring: Progressive delivery through Argo CD, including canary and blue/green, automated verification, and fast rollback, so a bad change is contained in minutes rather than escalated.
• Release management at pace: Coordinating what ships and when across [N] services, with change gates that catch problems without becoming a queue.
• Helm as a product, not a pile of charts: Reusable, tested, versioned charts that other teams can depend on.
• Incident response and what happens after: Leading incidents on the platform, then writing the postmortem and landing the follow-up work.
• Removing toil rather than absorbing it: Every recurring manual task is a candidate for automation in Python, Bash, or Ansible.
• Deciding what AI should and shouldn't touch in our delivery path: Reviewing AI-authored Helm and pipeline code before it reaches production, keeping secrets and customer data out of agent context, and scoping the credentials our CI agents hold.

Roles & Responsibilities:

• Service level management: Define and operate SLIs, SLOs, and error budgets for platform services; make reliability legible to engineering and product; drive the follow-through when budgets are burned.
• Production on-call and incident response: Hold primary on-call, act as incident commander, and run blameless postmortems with tracked actions. Escalate cleanly to Infra SecOps where infrastructure or credential changes are required. Use AI-assisted analysis to improve triage, root-cause identification, anomaly detection, and MTTR.
• Observability: Build and maintain the instrumentation, SLO monitors, and dashboards in Datadog that make failure visible before customers see it; reduce alert noise as deliberately as you add alerts.
• CI/CD engineering: Design, operate, and optimise build and deployment pipelines, including caching, parallel execution, automated testing, security scanning, and deployment verification. Manage artifacts and dependencies in the Artifactory.
• Release management and progressive delivery: Own the release process end-to-end; implement GitOps with Argo CD including canary and blue/green rollouts, automated validation, and rollback.
• Helm and deployment configuration: Build and maintain production-grade Helm charts and libraries with testing, versioning, policy validation, and reusable standards across services.
• Kubernetes day-2 operations: Operate and troubleshoot production Kubernetes, including scheduling, autoscaling, resource management, add-on lifecycle, and workload networking. Partner with Infra SecOps on upgrades and capacity changes.
• Toil reduction and automation: Identify and eliminate recurring operational work with automation in Python, Bash, and Ansible.
• Capacity and resilience: Workload-level capacity planning and resource tuning, resilience and failover testing, and feeding infrastructure capacity requirements into Infra SecOps ahead of need.
• AI guardrails and review: Define how AI-generated deployment and pipeline code is reviewed before it reaches production, keep secrets and customer data out of prompts and agent context, scope CI agent credentials to least privilege, and maintain provenance for generated code.
• Cross-team partnership: Review and raise pull requests against Infra SecOps' Terraform where platform changes are needed, and keep the interface between the two teams working.
• Technical leadership: Contribute to design and architecture reviews, mentor engineers, and raise the bar on availability, deployment speed, and developer experience.

Mandatory Skills:

• Production on-call ownership: You have held the pager for a SaaS platform, led incidents end-to-end, and written the postmortems.
• SLO practice: You have defined SLIs and SLOs for real services and can describe a decision and an error budget change.
• Kubernetes in production: Deep, hands-on day-2 operation and troubleshooting of EKS, including scheduling, autoscaling, resource management, and add-ons.
• Helm depth: You have written charts and libraries that other teams depend on, with tests and CI behind them.
• CI/CD engineering: You have built and owned pipelines at scale and can explain what you did to make them fast and trustworthy.
• Release engineering judgement: Practical experience with progressive delivery and rollback using Argo CD, Flux, or equivalent.
• Observability: Hands-on experience with Datadog or equivalent, including building monitors and dashboards.
• Systems fundamentals: Strong Linux, load balancing, and application clustering; you can debug from logs, stack traces, and core dumps.
• Demonstrated AI-assisted workflow: Examples of an agent or MCP integration, a prompt/context library, or an AI-assisted review or incident workflow, and where you decided not to use AI.
• Works well across a boundary: You have operated in a model where some remediation needs another team, and you know how to make that fast.

What Do We Offer?:

• Interesting Work: This is a challenge-yourself role where you learn something new every day, keep growing, and have fun doing it.
• Tribe Vibe: Spontaneous office happy hours, organized outings, and community volunteer opportunities in a diverse and distributed team.
• Bragging Rights: Work with prestigious brands across retail, airlines, and professional sports, including AirFrance KLM, ASICS, Burberry, Mattel, Mitsubishi, and Walmart.
• One Team One Dream: A value that means no artificial hierarchies, with regular updates about the business and its performance.