Cloud Engineer
- Role
- DevOps
- Experience
- Senior
- Employment
- Full-time
- Company size
- Enterprise
Open to IN only. Set where you work from to check your eligibility.
No BS summary
Seasoned Cloud Engineer with 7+ years in DevOps and cloud, strong AWS/Azure/GCP, Kubernetes, Docker, CI/CD, IaC, Python and shell scripting. Needs experience building cloud-native infrastructure and deployment pipelines for AI model/platform environments.
Core skills
Required skills
WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.
Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.
Role Overview:
We are seeking a seasoned Cloud Engineer to join our dynamic Technology research team. The ideal candidate will work collaboratively with the AI, Product and other teams to optimize building Devops cloud-based pipelines, enabling cloud infrastructure and services, ensuring the full benefits of standardized Cloud Tools are achieved across various teams of the vertical. This individual will play a crucial role in developing Infrastructure as a Code, AI models deployment pipelines, security ops, automating CI/CD pipelines, and streamlining cloud operations to improve efficiency, reduce costs, and enhance system availability, performance, and scalability.
Responsibilities:
- Be an active member of the team to build, own cloud based platform, its services, Devops pipelines for AI Model deployment, development pipelines, and provisioning public Cloud Native platform infrastructure in AWS or Azure or GCP.
- Develop and maintain Infrastructure as a Code (IaC) scripts to deploy cloud resources through pipelines and automate application installs.
- Continually evolve deployment methods and processes to effectively deliver products across all environments.
- Will be responsible for building docker containerization pipelines for Nvidia Nemo/NIM models and services.
- Will be involved in Containerization and Containers orchestration using Kubernetes
- Good experience in setting up end to end CI/CD using AWS/Azure Devops (components such as web app, function app, logic app and APIM)
- Building feedback loops to transfer data from client end to optimization hub in WNS environment. Will be involved in integrating platform with other tools like Junit, Jmeter, Jira, Jenkins etc
- Will be involved in sandbox cloud VM creation and replication for multiple users where they can collaborate to dev AI/Agentic AI applications.
- Will be involved in scaling product deployment - Authentication, Authorization, Session management, rest APIs and code building to scale applications which can be used by 10K+ users.
- Should have experience with AI Model versioning, code versioning through SVN and Git repository configuration and management
- Collaborate with the senior members of the AI Software Engineering team, Product Manager, and Product team to continuously improve the processes for the implementation, operation, and maintenance of the platform
- Implement automation, monitoring, logging, alerting, and deployment solutions to improve buildAI Model deployment experience and developer productivity.
- Ensure that all cloud solutions follow internally defined security and compliance standards and controls. Also take care of Containers and Code security while deploying the product/solution in client environment.
- Being the Cloud Native advocate to challenge status quo and ensure leveraging the full capabilities of the Cloud Platform
Skills:
- Possess one or more experience(AWS/Azure/GCP).
- Possess experience in containers development, Kubernetes, Devops tools, CI/CD pipeline development, Jenkins etc.
- Possess deep and broad knowledge and experience in general IT and public cloud, including Networking, Infrastructure, Security, Storage, Operating Systems (Linux/Windows).
- Experience with cloud infrastructure as code tooling.5. Proficiency in server OS, including Windows and/or Linux.6. Strong skills in Python and PowerShell/Bash scripting.
- Bachelors or master’s in computer science, Artificial Intelligence, or a related field
- 7+ years of experience in Devops and Cloud
- Experience tool chaining (GitHub, Jira), building CICD Pipeline, deployment automation, and containerization (Kubernetes, Docker).
- Excellent problem solving, troubleshooting and analytical skill
What you'll do
- Be an active member of the team to build, own cloud based platform, its services, Devops pipelines for AI Model deployment, development pipelines, and provisioning public Cloud Native platform infrastructure in AWS or Azure or GCP.
- Develop and maintain Infrastructure as a Code (IaC) scripts to deploy cloud resources through pipelines and automate application installs.
- Continually evolve deployment methods and processes to effectively deliver products across all environments.
- Will be responsible for building docker containerization pipelines for Nvidia Nemo/NIM models and services.
- Will be involved in Containerization and Containers orchestration using Kubernetes
- Good experience in setting up end to end CI/CD using AWS/Azure Devops (components such as web app, function app, logic app and APIM)
- Building feedback loops to transfer data from client end to optimization hub in WNS environment.
- Will be involved in integrating platform with other tools like Junit, Jmeter, Jira, Jenkins etc
- Will be involved in sandbox cloud VM creation and replication for multiple users where they can collaborate to dev AI/Agentic AI applications.
- Will be involved in scaling product deployment - Authentication, Authorization, Session management, rest APIs and code building to scale applications which can be used by 10K+ users.
- Collaborate with the senior members of the AI Software Engineering team, Product Manager, and Product team to continuously improve the processes for the implementation, operation, and maintenance of the platform
- Implement automation, monitoring, logging, alerting, and deployment solutions to improve buildAI Model deployment experience and developer productivity.
- Ensure that all cloud solutions follow internally defined security and compliance standards and controls.
- Also take care of Containers and Code security while deploying the product/solution in client environment.
- Being the Cloud Native advocate to challenge status quo and ensure leveraging the full capabilities of the Cloud Platform
What they require
- We are seeking a seasoned Cloud Engineer to join our dynamic Technology research team.
- The ideal candidate will work collaboratively with the AI, Product and other teams to optimize building Devops cloud-based pipelines, enabling cloud infrastructure and services, ensuring the full benefits of standardized Cloud Tools are achieved across various teams of the vertical.
- Possess one or more experience(AWS/Azure/GCP).
- Possess experience in containers development, Kubernetes, Devops tools, CI/CD pipeline development, Jenkins etc.
- Possess deep and broad knowledge and experience in general IT and public cloud, including Networking, Infrastructure, Security, Storage, Operating Systems (Linux/Windows).
- Experience with cloud infrastructure as code tooling.
- Proficiency in server OS, including Windows and/or Linux.
- Strong skills in Python and PowerShell/Bash scripting.
- Bachelors or master’s in computer science, Artificial Intelligence, or a related field
- 7+ years of experience in Devops and Cloud
- Experience tool chaining (GitHub, Jira), building CICD Pipeline, deployment automation, and containerization (Kubernetes, Docker).
- Excellent problem solving, troubleshooting and analytical skill
- Should have experience with AI Model versioning, code versioning through SVN and Git repository configuration and management
WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality.