Your Starting Advantage: You already have production-grade depth — Kubernetes operators, multi-cloud (AWS/Azure/GCP), ArgoCD, Argo Workflows, and Go. The gap isn't knowledge — it's demonstrable, differentiated projects and system design storytelling at scale. This roadmap closes that gap.
Piyush Jajoo piyushjajoo
piyushjajoo
/ faang-6-month-engineering-roadmap.md
Created
March 13, 2026 04:06
FAANG 6-Month Engineering Roadmap
piyushjajoo
/ ai-ml-platform-engineer-6-month-learning-roadmap.md
Last active
April 5, 2026 13:12
🚀 AI/ML Platform Engineer — 6-Month Learning Roadmap
For Kubernetes/Cloud Engineers transitioning into AI/ML Engineering Updated with: Data Engineering foundations, Vector DBs, LLMOps, Distributed Training, Security & Governance, ML Observability Resources listed in the order you should follow them.
You can't be an ML Platform Engineer without understanding the data layer. Start both tracks in parallel.
piyushjajoo
/ irsa-in-eks-within-and-across-aws-accounts.md
Created
August 4, 2023 16:05
IRSA in EKS within same and across AWS Accounts
This is a gist of examples also mentioned in the blog IAM Roles for Service Accounts (IRSA) in AWS EKS within and cross AWS Accounts. Prerequisite for this gist is to create the EKS Cluster as explained in my earlier blog Create Amazon EKS Cluster within its VPC using Terraform, OR you can use this github repository.
Assuming you have the EKS Cluster running and your AWS CLI is configured to talk to the AWS Account where your EKS Cluster is running. If not please follow the our earlier blog on How to create an EKS Cluster using Terraform