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SRE Devops Engineer

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Hybrid

SRE Devops Engineer

Cognizant

SRE Devops Engineer

Skills

Google Cloud PlatformE-commerce WebsitesMicroservicesKafkaGraphQLAIKubernetesSupply ChainTerraform

2 months ago

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Important information


Contract type:

Permanent

Location:

India

Work mode:

Hybrid

Published on:

18 August 2026

What they need


Role & responsibilities

  • Proven track record in SRE, DevOps, and Infrastructure, with significant tenure in the Retail or Supply Chain sector.
  • SRE Implementation: Direct experience building SRE organizations "from scratch" within large, complex enterprise environments.
  • Modern AI Stack: Expert knowledge in utilizing LLMs and AI Agents to accelerate SRE delivery, specifically for incident remediation and predictive maintenance.
  • Hybrid Networking: Deep understanding of on-prem retail hardware constraints, local networking, and thin/thick client architecture.
  • Middleware Mastery: Hands-on experience with Kafka, GraphQL, and microservices at scale.
  • Cloud Fluency: Advanced proficiency in Google Cloud Platform (GCP) or multi-cloud environments, including Kubernetes (GKE/EKS) and IaC (Terraform).
  • Strategic SRE Roadmap: Build and execute a multi-year SRE strategy from the ground up for a global retail enterprise, transitioning from legacy operations to a modern SLO-based culture.
  • Enterprise Reliability: Own the availability, latency, and performance of a complex omnichannel ecosystem, including high-traffic e-commerce Web Apps, APIs, and GraphQL layers.
  • Infrastructure Modernization: Orchestrate the reliability of a hybrid environment, bridging modern Cloud-native stacks with on-prem "Thin and Thick" retail store clients.
  • Event-Driven Architecture: Manage and scale high-throughput Kafka clusters and Event-Driven Architectures (EDA) to ensure seamless real-time data flow across global inventory and POS systems.
  • Observability Excellence: Standardize and oversee enterprise-wide monitoring and distributed tracing using DynaTrace, New Relic, and Google Cloud Monitoring.
  • AI-Enhanced Operations: Architect and deploy Agentic AI workflows and LLM-based solutions using MCP (Model Context Protocol) servers to automate root cause analysis, toil reduction, and self-healing.

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