- Design scalable CI/CD pipelines supporting multi-cloud and on-prem environments, using tools like ArgoCD, Jenkins, or Tekton.

Kubernetes and Container Orchestration :

- Deploy, manage, and troubleshoot Kubernetes clusters on AWS, OpenStack, or hybrid environments.

- Optimize cluster scaling and cost management using tools like Karpenter.

Cloud and Hybrid Infrastructure Management :

- Design, implement, and manage systems using AWS (preferred), GCP, Azure, OpenStack, or vSphere.

- Infuse AI into deployment processes for predictive canary analysis, rollback intelligence, and zero-downtime deployments.

- Build observability features enhanced with AI for log summarization, anomaly detection, event correlation, and proactive alerting.

- Automate vulnerability detection, prioritization, and remediation using AI-based classifiers and scanners.

- Use LLMs to generate security patches and improve infrastructure-as-code hygiene (e.g., Terraform misconfig detection and fix suggestions).

Must have :

- Expertise in cloud architecture, either full-stack development, or platform engineering.

- At least 2+ years working with AI/ML in engineering workflows (e.g., Copilot, CodeWhisperer, or custom LLM-based assistants).

- Demonstrated success building or integrating AI-enhanced developer or platform tools.

- Expertise in Kubernetes and Container Orchestration.

- Cloud and Hybrid Infrastructure Management: Design, implement, and manage systems using AWS.

Good to have :

- CI/CD tools like ArgoCD, Tekton, Jenkins.

- Infrastructure-as-code (Terraform, Crossplane).

- Full-stack technologies (React or Vue.js, Node.js, Python, Java).

- Observability and logging (Prometheus, OpenTelemetry, Datadog, ELK).