Delivery Lead

Senior DevOps Engineer / DevOps Architect eCommerce & AI-Enabled DevOps Experience: 15+ Years | Domain: eCommerce / Digital Commerce | Role: Senior Technical / Architecture Parttime: 50 hours/Month Role Overview 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.

1. DevOps & Cloud Architecture 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.

2. AWS & Google Cloud Platform 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.

3. Kubernetes & Docker 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.

4. Infrastructure & Networking 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, 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.

5. CI/CD & Release Automation 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.

6. Infrastructure as Code 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.

7. AI-Driven DevOps / AIOps 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.

8. AI-Enabled CI/CD 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.

9. AI-Based Production Support 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.

10. eCommerce DevOps Expertise 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.

11. Monitoring & Observability 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.

12. Security & DevSecOps 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.

13. Production & Incident Management 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.

14. Technical Leadership 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.

Required Technical Skills 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 AI / DevOps Skill Expectations 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.

Key Success Metrics 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.

Ideal Candidate Profile 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.

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