Senior Platform Engineer

CUBE Content Governance Global Limited; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

CUBE Content Governance Global Limited is seeking a seasoned Platform Engineer to design, build, and operate cloud-native platform services on Microsoft Azure, with AKS-based runtimes and self-service capabilities.

You will implement infrastructure as code (Terraform) and GitOps workflows, contribute to CI/CD pipelines with Azure DevOps and GitHub Actions, and mentor junior engineers while driving reliability, security, and cost governance across data, ML, and software workloads.

Qualifications

• 4–6 years of strong experience in cloud engineering with hands-on Azure expertise.
• Production experience operating AKS at scale.
• Advanced use of Terraform for provisioning and governance.
• Strong knowledge of Helm for Kubernetes workload configuration.
• Experience building CI/CD pipelines with Azure DevOps and/or GitHub Actions.
• Solid understanding of cloud networking, Azure AD identity, and security controls.
• Experience designing self-service platforms and reliable patterns.
• Reliability engineering, incident management, and change control in production.

Responsibilities

• Design, build, and operate shared platform services on Microsoft Azure with AKS-based runtimes.
• Develop reusable infrastructure modules (Terraform, Helm) for self-service by apps, data, and ML teams.
• Own platform components end-to-end, including availability, performance, and security.
• Define platform standards and golden paths for workload onboarding and scaling.
• Implement IaC and GitOps workflows for platform changes.
• Contribute to CI/CD pipelines using Azure DevOps and GitHub Actions with automated validation and rollbacks.
• Reduce manual effort via automation and opinionated defaults.
• Ensure services meet SLOs, security controls, and resilience standards.
• Implement observability with tools like New Relic (metrics, logs, alerts, dashboards).
• Lead or support incident investigations and post-incident reviews.
• Support DataOps and MLOps workloads with secure, scalable platforms.
• Collaborate with data/AI teams on Fabric, data platforms, and ML tooling.
• Mentor junior engineers and share platform engineering best practices.

Skills

Microsoft Azure

AKS

Terraform

Helm

CI/CD pipelines

Azure DevOps

GitHub Actions

Networking

Identity & security

Observability

New Relic

DataOps/MLOps

Tools

Terraform

Helm

Azure DevOps

GitHub Actions

New Relic

Job description

Purpose

This role focuses on cloud‑native platform engineering: building self‑service infrastructure, standardised deployment patterns, and reliable runtime platforms on Azure. You will work closely with software, data, and ML teams to provide guardrails, automation, and operational excellence across the full system lifecycle.

Key Responsibilities

• Design, build, and operate shared platform services on Microsoft Azure, with a strong focus on AKS‑based runtime platforms.
• Develop and maintain reusable infrastructure and platform modules (Terraform, Helm) that enable safe self‑service by application, data, and ML teams.
• Own platform components end‑to‑end (build–run), including availability, performance, security, cost, and operability.
• Define and evolve platform standards and golden paths for workload onboarding, networking, identity, secrets, observability, and scaling.
• Implement infrastructure and platform changes using Infrastructure as Code (Terraform) and GitOps‑style workflows.
• Contribute to and improve CI/CD pipelines using Azure DevOps and GitHub Actions, including automated validation, approvals, and rollbacks.
• Reduce manual operational effort through automation, self‑service tooling, and opinionated defaults.
• Ensure platform services meet agreed SLOs, security controls, compliance requirements, and resilience standards.
• Implement and maintain observability using New Relic, including metrics, logs, alerts, and dashboards.
• Lead or support investigation and resolution of complex platform incidents; contribute to post‑incident reviews and systemic improvements.
• Design and validate backup, recovery, and disaster recovery mechanisms for platform‑managed services.
• Enable application teams with reliable deployment and runtime patterns (e.g. ingress, service mesh, secrets, scaling, CI/CD integration).
• Support DataOps and MLOps workloads by providing secure, scalable platforms for data pipelines, model training, and inference.
• Collaborate with data and AI teams on services such as Microsoft Fabric, data platforms, and ML lifecycle tooling.
• Act as a senior technical partner to software engineers, data engineers, and ML engineers.
• Provide technical input into solution and service design, ensuring operational and platform considerations are addressed early.
• Mentor and support junior and mid‑level engineers, sharing platform engineering best practices.
• Contribute to continuous improvement of platform processes, documentation, and standards.

Skills & Competencies

• Someone with 4‑6 years of strong experience in cloud engineering, with hands‑on expertise in Microsoft Azure.
• Production experience operating Azure Kubernetes Service (AKS) at scale.
• Advanced use of Terraform for infrastructure and platform provisioning (modules, state management, governance).
• Strong working knowledge of Helm for Kubernetes workload and platform configuration.
• Experience building and operating CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Solid understanding of cloud networking, identity (Azure AD / Managed Identity), private endpoints, and security controls.
• Experience designing self‑service platforms or reusable infrastructure patterns.
• Strong understanding of reliability engineering, incident management, and change control in production environments.
• Practical experience with observability and monitoring, ideally with New Relic or equivalent tools.
• Ability to balance delivery speed with risk management, stability, and long‑term sustainability.
• Clear communicator, able to explain technical trade‑offs and risks to both technical and non‑technical stakeholders.
• Comfortable working autonomously within a defined platform scope.
• Strong sense of ownership and accountability for platform outcomes.
• Exposure to DataOps or MLOps practices, tooling, or platforms.
• Experience supporting data pipelines, lakehouse architectures, or ML workloads on cloud platforms.
• Familiarity with Microsoft Fabric, ML pipelines, model deployment, or feature stores.

Required Experience & Qualifications

• Relevant experience, training, or demonstrated capability for the role's track, domain, and level.
• Practical understanding of the tools, methods, governance, and delivery practices used in the role.
• Ability to work effectively with relevant stakeholders and contribute to reliable, high‑quality outcomes.
• Relevant degree, professional qualification, certification, apprenticeship, or equivalent experience is desirable where applicable.

Performance Indicators

• High availability and reliability of platform services used by delivery teams.
• Safe, repeatable, and automated platform changes with minimal unplanned incidents.
• Improved developer, data, and ML team experience through self‑service and standardisation.
• Reduction in platform‑related incidents, toil, or technical debt over time.
• Positive feedback from engineering teams on platform usability and support.

CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.