AWS-first platform engineer with 4+ years of experience across Kubernetes, Terraform, CI/CD, GitOps, SRE and production operations. Building secure, observable and automated infrastructure for cloud-native and machine-learning workloads.
Senior DevOps Engineer | ML Platform & MLOps Infrastructure
My strongest lane is DevOps to Platform Engineering to ML Platform Engineering to MLOps. I focus on the infrastructure, deployment, reliability, observability, governance and lifecycle automation needed to operate production systems and ML workloads.
| Area | Tools and practices |
|---|---|
| Cloud | AWS, EKS, EC2, VPC, IAM, S3, RDS, CloudWatch, Azure/GCP exposure |
| Containers and GitOps | Kubernetes, Docker, Helm, Argo CD, Kustomize |
| IaC and automation | Terraform, Terragrunt, Ansible, Python, Boto3, Bash |
| CI/CD | GitHub Actions, GitLab CI/CD, Jenkins, AWS CodePipeline |
| SRE and observability | Prometheus, Grafana, CloudWatch, ELK, SLO/SLI, incident response, RCA |
| ML platform | MLflow, Kubeflow workflow support, FastAPI model serving, model registry handoff, monitoring, rollback patterns |
| Security and governance | RBAC, IAM, NetworkPolicy, Kyverno, OPA, Trivy, secrets management, cost optimisation |
| Project | Focus | What it demonstrates |
|---|---|---|
| aws-eks-platform-blueprint | AWS/EKS platform engineering | Terraform VPC/EKS blueprint, GitOps, autoscaling, RBAC, Prometheus/Grafana/Loki |
| ml-platform-infrastructure-on-kubernetes | ML platform infrastructure | FastAPI model serving, Docker, Helm, Argo CD, MLflow flow, metrics and rollback docs |
| terraform-gitops-delivery-platform | IaC delivery platform | Multi-environment Terraform, CI validation, OPA policy examples, Kustomize and Argo CD promotion |
| sre-observability-incident-response-lab | SRE and incident response | Instrumented Python service, SLOs, alerts, dashboards, synthetic checks, runbooks and RCA templates |
| secure-kubernetes-platform-hardening | Kubernetes security | Pod Security Standards, NetworkPolicies, RBAC, Kyverno, OPA, secret templates and Trivy CI |
| cloud-cost-optimization-toolkit | Cloud automation and FinOps | Python CLI for idle resources, missing tags, oversized resources, dry-run reports and optional Boto3 inventory |
Two additional public repositories support the same direction:
| Project | Focus | What it demonstrates |
|---|---|---|
| devops-policy-audit-toolkit | DevOps policy automation | CLI checks for Terraform, Kubernetes, IAM, Dockerfiles, GitHub Actions and report generation |
| rental-price-mlops-pipeline | End-to-end MLOps pipeline | Data validation, model quality gates, model artifact packaging, registry metadata, FastAPI serving and Kubernetes deployment |
I keep earlier computer-vision and AI repositories public as learning and research archives, but my current market focus is DevOps, Platform Engineering, SRE and ML platform infrastructure.
- Designing AWS EKS platforms with Terraform, IAM, networking and observability.
- Building GitOps delivery flows with CI validation, Helm/Kustomize and Argo CD.
- Operating services with SLOs, alerts, runbooks, RCA and incident response discipline.
- Securing Kubernetes with RBAC, NetworkPolicy, Pod Security Standards and admission controls.
- Bridging DevOps into MLOps through model serving, registry handoffs, monitoring and rollback patterns.