Senior DevOps Engineer / DevOps Architect
eCommerce & AI-Enabled DevOps
Experience: 15+ Years | Domain: eCommerce / Digital Commerce | Role: Senior Technical / Architecture
Parttime: 50 hours/Month
We are looking for a highly experienced Senior DevOps Engineer / DevOps Architect with 15+ years of experience in enterprise eCommerce and digital commerce environments. The candidate should have strong hands-on and architectural expertise across AWS, Google Cloud Platform, Docker, Kubernetes, Infrastructure, CI/CD, Infrastructure as Code, Cloud Security, Monitoring, and Production Operations. The ideal candidate should also have practical experience in AI-enabled DevOps, including Generative AI, AI agents, AIOps, intelligent automation, predictive monitoring, automated incident analysis, and AI-assisted software delivery.
· Define and implement scalable, secure, highly available DevOps and Cloud architectures for enterprise eCommerce platforms.
· Design and manage cloud environments across AWS and Google Cloud Platform.
· Define architecture for Development, QA, UAT, Pre-Production, and Production environments.
· Design solutions covering compute, storage, networking, load balancing, CDN, DNS, databases, caching, security, monitoring, and disaster recovery.
· Drive cloud modernization and migration initiatives.
· Perform capacity planning and infrastructure optimization for high-volume eCommerce platforms.
· Strong hands-on experience with AWS services including EC2, ECS/EKS, Lambda, S3, RDS, DynamoDB, ElastiCache, CloudFront, Route 53, API Gateway, CloudWatch, IAM, VPC, ALB/NLB, WAF, and Secrets Manager.
· Experience with Google Cloud Platform services including GKE, Compute Engine, Cloud Storage, Cloud SQL, Cloud Load Balancing, Cloud CDN, Cloud Monitoring, IAM, VPC, and Secret Manager.
· Experience with multi-cloud architecture and workload optimization is preferred.
· Design, deploy, and manage enterprise Kubernetes environments.
· Strong experience with AWS EKS and Google Cloud Platform GKE.
· Develop and manage Docker containers and containerized applications.
· Work with Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, StatefulSets, Helm, HPA, and Persistent Volumes.
· Implement container security and image management.
· Troubleshoot Kubernetes cluster, application, networking, and performance issues.
· Implement autoscaling and resilient container architectures.
· Strong understanding of Linux/Unix administration, web/application servers, database infrastructure, storage, compute, virtualization, load balancers, high availability, disaster recovery, backup/restoration, and capacity planning.
· Strong networking knowledge covering TCP/IP, DNS, HTTP/HTTPS, SSL/TLS, VPN, VPC/VNet, subnets, routing, NAT, firewalls, security groups, WAF, CDN, proxy, and load balancing.
· Ability to troubleshoot issues across application, container, cloud, infrastructure, and network layers.
· Design and implement enterprise CI/CD pipelines.
· Automate build, testing, security scanning, deployment, rollback, and release processes.
· Experience with Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps, and Argo CD.
· Implement Blue/Green, Canary, Rolling, and zero-downtime deployments.
· Integrate automated testing and security gates into pipelines.
· Improve deployment frequency, release quality, and engineering productivity.
· Strong experience with Terraform and/or CloudFormation.
· Create reusable infrastructure modules and automate cloud provisioning.
· Manage infrastructure through Git-based version control.
· Establish enterprise IaC standards and governance.
· Automate environment creation and configuration.
· Use Generative AI tools to accelerate infrastructure scripting, Terraform development, Kubernetes configuration, CI/CD pipeline creation, shell/Python scripting, troubleshooting, and documentation.
· Design or implement AI agents for automated log analysis, incident investigation, Root Cause Analysis, infrastructure health checks, deployment validation, CI/CD failure analysis, automated remediation, performance analysis, security issue identification, environment validation, and release readiness checks.
· Implement AIOps capabilities including predictive monitoring, anomaly detection, intelligent alert correlation, incident prediction, event correlation, automated RCA, capacity forecasting, performance optimization, intelligent ticket classification, and automated incident response.
· Drive intelligent CI/CD pipelines using AI.
· Implement workflows such as Code Commit → AI Code Analysis → Build → Automated Testing → Security Scan → AI Risk Analysis → Deployment → AI Deployment Validation → Monitoring → Automated Remediation.
· Use AI to identify high-risk deployments, potential production issues, failed deployment patterns, infrastructure configuration issues, performance degradation, and security vulnerabilities.
· Build AI-driven production monitoring and support capabilities.
· Implement intelligent analysis of application and infrastructure logs.
· Correlate logs, metrics, traces, alerts, deployment history, and infrastructure changes using AI.
· Develop automated RCA and incident-summary generation.
· Build self-healing capabilities where appropriate.
· Reduce MTTR through intelligent incident diagnosis and automation.
· Strong understanding of DevOps requirements for enterprise eCommerce platforms such as Salesforce Commerce Cloud, HCL Commerce, Adobe Commerce/Magento, SAP Commerce/Hybris, Medusa Commerce, and custom Java/Node.js commerce platforms.
· Experience with product catalog, search, inventory, order management, payment systems, API integrations, microservices, Redis/cache, Elasticsearch/Solr, CDN, databases, batch processing, and third-party integrations.
· Understand peak traffic, flash sales, promotional events, Black Friday/holiday traffic, performance testing, autoscaling, and high availability.
· Implement enterprise observability using Prometheus, Grafana, ELK/Elastic, Splunk, Datadog, New Relic, CloudWatch, and Cloud Monitoring.
· Implement infrastructure, application, Kubernetes, distributed tracing, log aggregation, alert management, SLI/SLO monitoring, and performance dashboards.
· Leverage AI for intelligent alerting, anomaly detection, and predictive monitoring.
· Implement DevSecOps practices across the SDLC.
· Integrate security scanning into CI/CD.
· Secure containers and Kubernetes clusters.
· Implement IAM and least-privilege access.
· Manage secrets and certificates securely.
· Implement vulnerability scanning and remediation.
· Support cloud security and compliance requirements.
· Provide technical leadership during P1/P2 production incidents.
· Perform detailed Root Cause Analysis and define permanent corrective actions.
· Support production releases and hypercare.
· Develop operational runbooks.
· Implement disaster recovery and business continuity processes.
· Drive reduction in MTTR, deployment failures, and production incidents.
· Lead and mentor DevOps and Infrastructure teams.
· Define enterprise DevOps standards and best practices.
· Conduct architecture and technical design reviews.
· Partner with Application, QA, Security, Architecture, and Delivery teams.
· Lead cloud migration and modernization initiatives.
· Support technical estimations, proposals, RFP/RFQ responses, and pre-sales activities.
· Define and drive AI-enabled DevOps transformation initiatives.
Area
Skills
Experience
15+ Years
Domain
eCommerce / Digital Commerce
Cloud
AWS, Google Cloud Platform
Containers
Docker, Kubernetes
Kubernetes
EKS, GKE, Helm, Ingress, HPA
IaC
Terraform, CloudFormation
CI/CD
Jenkins, GitHub Actions, GitLab, Argo CD
OS
Linux / Unix
Scripting
Shell/Bash, Python
Networking
TCP/IP, DNS, VPN, SSL, CDN, WAF, Load Balancers
Monitoring
Prometheus, Grafana, ELK, Datadog, New Relic
Security
IAM, DevSecOps, Secrets, Vulnerability Management
Version Control
Git, GitHub, GitLab, Bitbucket
AI / GenAI
Generative AI, AI Agents, AIOps, LLM-based automation
Automation
Infrastructure & Deployment Automation
eCommerce
Enterprise Commerce Platforms
· GenAI for DevOps: AI-assisted scripting, AI-generated Terraform/Kubernetes configurations, AI-assisted troubleshooting, and AI documentation.
· AI Agents: Incident Agent, Monitoring Agent, Deployment Agent, RCA Agent, Infrastructure Health Agent, and Release Validation Agent.
· AIOps: Anomaly Detection, Predictive Monitoring, Intelligent Alert Correlation, Automated RCA, and Auto-remediation.
· AI-Enabled SDLC: AI-based Code Review, Test Automation, Security Analysis, Deployment Risk Assessment, and Production Monitoring.
· 99.9%+ platform availability.
· Reduction in deployment failures and production incidents.
· Reduction in MTTR.
· Increased deployment frequency and automation coverage.
· Reduced manual infrastructure activities.
· Improved cloud infrastructure utilization and cost optimization.
· AI-driven reduction in DevOps operational effort.
· Faster incident identification and resolution.
· Improved production stability and scalability.
15+ Years | Enterprise eCommerce | AWS | Google Cloud Platform | Docker | Kubernetes | EKS/GKE | Terraform | CI/CD | Infrastructure | Networking | DevSecOps | Observability | AIOps | GenAI | AI Agents | Production Support | Cloud Architecture
Positioning: This is a Senior DevOps / DevOps Architect role with strong infrastructure ownership and AI transformation capability, rather than a conventional DevOps Engineer focused primarily on CI/CD.
