DevOps Engineer – Developer UX

• *Job Requirements**

• *Position Summary**

We are seeking a passionate and motivated DevOps Engineer with exposure to Developer Experience, AI, and Cloud Technologies to join our growing team. This role is ideal for professionals with 3\+ years of experience in DevOps, Cloud Infrastructure, Platform Engineering, or Site Reliability Engineering (SRE) who are looking to expand their expertise in AI infrastructure, automation, and cloud\-native technologies.

The successful candidate will shape the developer experience of our cloud infrastructure and deployment tools by driving automation and seamless self\-service provisioning, so development teams can use our environments and tools to deploy their services quickly, reliably, and with minimal manual effort.

• *Key Responsibilities**

Developer Experience \& Self\-Service

• Treat our cloud environments and deployment tools as internal products: understand the needs of development teams, collect feedback, and continuously improve usability.
• Design and build self\-service capabilities (e.g., templates, golden paths, portals, CLIs) that let teams using and provision environments and deploy services on demand without manual handoffs.
• Reduce friction and onboarding time by standardizing workflows, removing manual steps, and providing sensible defaults.
• Create and maintain clear, developer\-friendly documentation, examples, and onboarding guides.
• Measure and improve developer experience using metrics such as time\-to\-first\-deployment, provisioning lead time, and user satisfaction.

Cloud Infrastructure \& Platform Operations

• Design, deploy, and maintain cloud infrastructure on Azure or AWS.
• Operate Kubernetes and container platforms for application and AI workloads.
• Automate infrastructure provisioning with Infrastructure as Code (IaC).
• Build and maintain Helm charts for application deployments.
• Troubleshoot infrastructure, networking, and deployment issues.

DevOps \& Automation

• Build and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools.
• Automate operational tasks with PowerShell and C\#.
• Drive release management, deployment automation, and environment provisioning.
• Use AI\-powered tools to increase operational efficiency.

AI \& MLOps Support

• Deploy and monitor AI/ML applications and services.
• Maintain MLOps workflows with Azure ML, MLflow, or Kubeflow.
• Monitor performance of AI workloads and their infrastructure.

Monitoring \& Reliability

• Implement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud\-native tools.
• Resolve incidents, run root cause analyses, and optimize performance.
• Improve system reliability, scalability, and availability.

• *Required Technical Skills**

Developer Experience \& Platform Engineering

• Experience building self\-service tooling for development teams, such as templates, golden paths, CLIs or portals.
• Product mindset: you understand developer needs, gather feedback and keep improving usability.
• You write clear documentation and onboarding guides for developers.
• Experience measuring developer experience with DORA metrics, lead times or developer satisfaction.

Cloud Platforms

• Hands\-on experience with at least one cloud platform: Microsoft Azure (preferred), AWS or GCP.

Containers \& Orchestration

• Docker
• Kubernetes (basic to intermediate)
• Helm, including building reusable charts for teams to use

Infrastructure as Code

• Terraform and/or ARM Templates / Bicep, including building reusable modules
• Ansible (basic knowledge)

Programming \& Scripting

• Python, PowerShell, Bash, C\#
• Experience automating workflows and building developer tools

CI/CD \& Version Control

• Azure DevOps and/or GitHub Actions
• Git\-based workflows

Monitoring \& Logging

• Prometheus, Grafana, ELK Stack, Azure Monitor or similar tools

Operating systems

• Linux
• Windows

• *Preferred Qualifications**

• Bachelor's degree in Computer Science, IT, Engineering, or a related field.
• 3\+ years in DevOps, Platform Engineering, Cloud/Infrastructure Engineering, or SRE, ideally focused on developer tooling or internal platforms.
• Experience building self\-service tooling that makes provisioning and deployment easy for developers.
• Developer\-focused mindset, with strong communication and documentation skills.
• Hands\-on experience with Docker and Kubernetes.
• Solid understanding of CI/CD and deployment automation.
• Familiarity with Infrastructure as Code.
• Basic knowledge of AI/ML deployment and MLOps.
• Knowledge of cloud security and networking basics.
• Experience working in Agile teams.
• Azure, AWS, Kubernetes, or Terraform certifications are a plus.

• *Nice\-to\-Have Skills**

• Experience with internal developer platforms such as Backstage or Port.
• Knowledge of GitOps practices, such as Argo CD or Flux.
• Use of AI coding assistants and AI\-assisted operations (AIOps) to boost developer productivity.
• Exposure to Azure ML, Kubeflow or MLflow.
• Experience with container security and vulnerability management.
• Familiarity with distributed systems and microservices architectures.

• *Benefits**

DevOps Engineer – Developer UX

Location: Bengaluru, India

Experience: 3\-5 Years

• *Position Summary**

We are seeking a passionate and motivated DevOps Engineer with exposure to Developer Experience, AI, and Cloud Technologies to join our growing team. This role is ideal for professionals with 3\+ years of experience in DevOps, Cloud Infrastructure, Platform Engineering, or Site Reliability Engineering (SRE) who are looking to expand their expertise in AI infrastructure, automation, and cloud\-native technologies.

The successful candidate will shape the developer experience of our cloud infrastructure and deployment tools by driving automation and seamless self\-service provisioning, so development teams can use our environments and tools to deploy their services quickly, reliably, and with minimal manual effort.

• *Key Responsibilities**

Developer Experience \& Self\-Service

• Treat our cloud environments and deployment tools as internal products: understand the needs of development teams, collect feedback, and continuously improve usability.
• Design and build self\-service capabilities (e.g., templates, golden paths, portals, CLIs) that let teams using and provision environments and deploy services on demand without manual handoffs.
• Reduce friction and onboarding time by standardizing workflows, removing manual steps, and providing sensible defaults.
• Create and maintain clear, developer\-friendly documentation, examples, and onboarding guides.
• Measure and improve developer experience using metrics such as time\-to\-first\-deployment, provisioning lead time, and user satisfaction.

Cloud Infrastructure \& Platform Operations

• Design, deploy, and maintain cloud infrastructure on Azure or AWS.
• Operate Kubernetes and container platforms for application and AI workloads.
• Automate infrastructure provisioning with Infrastructure as Code (IaC).
• Build and maintain Helm charts for application deployments.
• Troubleshoot infrastructure, networking, and deployment issues.

DevOps \& Automation

• Build and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools.
• Automate operational tasks with PowerShell and C\#.
• Drive release management, deployment automation, and environment provisioning.
• Use AI\-powered tools to increase operational efficiency.

AI \& MLOps Support

• Deploy and monitor AI/ML applications and services.
• Maintain MLOps workflows with Azure ML, MLflow, or Kubeflow.
• Monitor performance of AI workloads and their infrastructure.

Monitoring \& Reliability

• Implement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud\-native tools.
• Resolve incidents, run root cause analyses, and optimize performance.
• Improve system reliability, scalability, and availability.

• *Required Technical Skills**

Developer Experience \& Platform Engineering

• Experience building self\-service tooling for development teams, such as templates, golden paths, CLIs or portals.
• Product mindset: you understand developer needs, gather feedback and keep improving usability.
• You write clear documentation and onboarding guides for developers.
• Experience measuring developer experience with DORA metrics, lead times or developer satisfaction.

Cloud Platforms

• Hands\-on experience with at least one cloud platform: Microsoft Azure (preferred), AWS or GCP.

Containers \& Orchestration

• Docker
• Kubernetes (basic to intermediate)
• Helm, including building reusable charts for teams to use

Infrastructure as Code

• Terraform and/or ARM Templates / Bicep, including building reusable modules
• Ansible (basic knowledge)

Programming \& Scripting

• Python, PowerShell, Bash, C\#
• Experience automating workflows and building developer tools

CI/CD \& Version Control

• Azure DevOps and/or GitHub Actions
• Git\-based workflows

Monitoring \& Logging

• Prometheus, Grafana, ELK Stack, Azure Monitor or similar tools

Operating systems

• Linux
• Windows

• *Preferred Qualifications**

• Bachelor's degree in Computer Science, IT, Engineering, or a related field.
• 3\+ years in DevOps, Platform Engineering, Cloud/Infrastructure Engineering, or SRE, ideally focused on developer tooling or internal platforms.
• Experience building self\-service tooling that makes provisioning and deployment easy for developers.
• Developer\-focused mindset, with strong communication and documentation skills.
• Hands\-on experience with Docker and Kubernetes.
• Solid understanding of CI/CD and deployment automation.
• Familiarity with Infrastructure as Code.
• Basic knowledge of AI/ML deployment and MLOps.
• Knowledge of cloud security and networking basics.
• Experience working in Agile teams.
• Azure, AWS, Kubernetes, or Terraform certifications are a plus.

• *Nice\-to\-Have Skills**

• Experience with internal developer platforms such as Backstage or Port.
• Knowledge of GitOps practices, such as Argo CD or Flux.
• Use of AI coding assistants and AI\-assisted operations (AIOps) to boost developer productivity.
• Exposure to Azure ML, Kubeflow or MLflow.
• Experience with container security and vulnerability management.
• Familiarity with distributed systems and microservices architectures.