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DevOps Engineer

DevOps Engineer

HCLSoftwareThiruvananthapuram, IN
17 hours ago
Job description

Senior DevOps Engineer

Location : Pune & Bangalore

Exp : 5+ years

Objective :

We are seeking a highly skilled and experienced Senior DevOps Engineer to lead the design, automation, and optimization of our cloud infrastructure on Azure . This role is critical to supporting a fast-growing, AI-driven Commerce platform. You will be responsible for building and maintaining robust CI / CD pipelines, ensuring secure and scalable operations for our microservices architecture, and collaborating with engineering and ML teams to streamline delivery and enable efficient multi-region deployments.

About HCL Software :

HCL Software is the software business division of HCLTech, fueling the Digital+ Economy by developing, sharing, and supporting solutions in five key areas :

  • Business & Industry Applications
  • AI and Intelligent Operations
  • Total Experience
  • Data & Analytics
  • Cybersecurity

These five solution areas represent massive opportunities for growth and enable total flexibility in deployment — efficiently managing data, applications, workloads, and infrastructure, leveraging our cloud options and the power of Gen AI.

About HCL Commerce :

HCL Commerce is a robust and scalable e-commerce platform that supports various business models including B2C, B2B, B2B2C, D2C, and MarketPlaces. Known for its enterprise-grade performance, HCL Commerce offers advanced features and AI capabilities to enhance online transactions and customer experiences.

Responsibilities

  • Infrastructure Architecture and Automation : Lead the end-to-end design, automation, and deployment of our cloud infrastructure on Azure using Infrastructure as Code (IaC) principles.
  • CI / CD Pipeline Management : Build, maintain, and optimize robust Azure DevOps pipelines, integrating build, test, security scanning (SAST / DAST / SCA), and automated promotion across all environments.
  • Azure Service Management : Own the management, optimization, and secure configuration of key Azure services, including AKS , Container Apps , API Management , Cosmos DB , Event Hub , Key Vault , and Application Gateway.
  • Observability and Monitoring : Define and implement a comprehensive observability strategy using App Insights , Log Analytics , and Grafana to create actionable dashboards and alerts for system health and performance.
  • Reliability and Scalability : Architect and manage multi-region deployments, ensuring high availability, disaster recovery (DR) readiness, and overall system resilience.
  • Cross-Functional Collaboration : Work closely with engineering and ML teams to streamline the integration and deployment of AI models and microservices into our production environments.
  • Continuous Improvement : Lead post-mortem and root cause analysis (RCA) efforts to drive continuous improvement in deployment reliability, performance, and security.
  • Qualifications

  • Experience : 7-12 years of experience in DevOps or Cloud Infrastructure Engineering, with at least 4+ years of deep, hands-on experience with Microsoft Azure .
  • Cloud & DevOps Expertise :
  • Deep hands-on experience with Azure DevOps , AKS (Azure Kubernetes Service), Container Apps , and APIM .
  • Strong knowledge of Infrastructure as Code ( IaC ), specifically Bicep and Terraform .
  • Proficiency with Kubernetes , Helm charts , Docker , and container-based deployment workflows.
  • Experience setting up monitoring, logging, and alerting pipelines ( App Insights , Log Analytics , Prometheus , Grafana ).
  • Understanding of Azure Identity, Security, and Key Vault integration.
  • Core Competencies :
  • Strong scripting skills in Bash, PowerShell, or Python for automation.
  • Experience designing and managing secure network topologies (VNets, Subnets, DNS Zones, Peering, Private Endpoints).
  • Proven expertise in CI / CD automation, release management, and environment governance.
  • Preferred Qualifications :
  • Experience with Databricks , Event Hub , or Cosmos DB integration for data / ML workloads.
  • Exposure to multi-region architecture and BCP / DR planning.
  • Experience managing agentic AI or ML model deployment pipelines.
  • Familiarity with orchestration tools like Dagster, Argo, or Airflow.
  • Knowledge of container security, OPA / Gatekeeper policies, and Azure Policy enforcement.
  • Experience supporting e-commerce or SaaS platforms at scale.
  • Education : Bachelor’s degree in Computer Science, Engineering, or a relevant field (or equivalent practical experience).
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