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This seat builds and runs the enterprise cloud infrastructure that Zscaler's production AI and machine learning workloads sit on. It is platform engineering rather than modelling: scalable, secure, highly available AWS infrastructure (EKS, Lambda, ECS, VPC, IAM) built with Terraform following infrastructure as code practice, GitLab CI/CD pipelines that automate build, test, security scanning and multi environment deployment, and a centralised observability stack on Prometheus and Grafana. You also drive platform governance so AI and data engineering teams can ship reliably and securely. It sits inside the IT Data Strategy team. Apply if you want MLOps and platform infrastructure work with real AWS depth, and note it is offered in Bangalore or Pune. Who it is for: Requirements. 8+ years of industry experience. Deep AWS infrastructure experience across EKS, Lambda, ECS, VPC and IAM. Terraform and infrastructure as code practice including reusable modules, remote state management and environment based blueprints. CI/CD pipeline ownership, with GitLab named. Observability tooling, with Prometheus and Grafana named. Responsibilities. Design, build and maintain scalable, secure and highly available AWS infrastructure for AI and ML workloads using Terraform, following IaC best practice including reusable modules, remote state management and environment based blueprints. Own and continuously evolve GitLab CI/CD pipelines for AI platform services, automating build, test, security scanning and multi environment deployment so releases are fast, reliable and repeatable. Architect a centralised observability stack using Prometheus and Grafana. Drive infrastructure automation, observability and platform governance so AI and data engineering teams can deliver reliably and securely. Where it sits. The posting places this in the IT Data Strategy team. That is internal platform engineering serving the company's own AI and data teams, rather than customer facing product work. It is genuine infrastructure engineering rather than end user IT support, which is why it is in scope here. Location. Bangalore or Pune, both listed, which is worth noting since almost every role in this edition is Bangalore only. Zscaler operates a hybrid model. Who this is for. A platform or DevOps engineer with eight or more years who wants to specialise toward AI infrastructure. The AWS and Terraform requirements are the hard ones; the AI part is about supporting ML workloads rather than building models, so you do not need a machine learning background to be credible here. Pune as an option makes this accessible if Bangalore does not suit you. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.