New opportunity

Software Engineer - AI Hub

Praxair India Private Limited · Bangalore, India

About this role

Role Purpose: As a Software Engineer in the AI Hub, you will support Linde's global initiatives by extending existing products and building new cloud-based applications for diverse use cases across the company's value chain. You will work directly with customer data to develop platforms and products for internal customers. Responsibilities: Develop and maintain new and existing platforms; build and experiment with CI/CD tooling for reliable software delivery; perform reliability and performance testing; establish process management tools and application monitoring; and develop prototypes and replication pipelines to connect existing solutions to other systems. Qualifications: Educational background in Computer Science, Engineering, or a related technical field. Hands-on experience with the end-to-end software development lifecycle. Proficiency in modern programming languages, specifically Python. Strong foundation in version control, automated testing, and writing maintainable code. Practical exposure to cloud-native architectures, containerization (Docker, Kubernetes), and building solutions on Azure. Familiarity with Infrastructure as Code and deployment workflows such as Helm, ArgoCD, and Bicep. Strong communication skills and ability to collaborate with distributed engineering teams across multiple time zones.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

PythonCloud-native architecturesDockerKubernetesAzureInfrastructure as CodeHelmArgoCDBicepCI/CDSoftware development lifecycleVersion controlAutomated testing

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Cloud-Native Application Development
The role requires building and extending cloud-based applications on Azure. You must demonstrate proficiency in designing scalable, containerized solutions using Docker and Kubernetes to support Linde's global business value chain.
Reliable CI/CD and Infrastructure Automation
A core priority is establishing robust deployment workflows. You will be expected to utilize Infrastructure as Code (IaC) tools like Bicep, Helm, and ArgoCD to ensure reliable, automated software delivery and consistent environment management.
System Reliability and Performance Monitoring
Beyond feature development, you must implement application monitoring and perform reliability testing. This ensures that the platforms built for internal customers remain performant and stable under operational loads.

Likely challenges to think through

Cross-Time Zone Collaboration
As part of a global AI team, you will collaborate with distributed engineering teams. The challenge lies in maintaining alignment and communication efficiency across different time zones; prepare by highlighting your experience with asynchronous documentation and structured communication tools.
Integrating Prototypes into Production Pipelines
You are tasked with building replication pipelines to connect prototypes to existing systems. This requires balancing rapid experimentation with the need for maintainable, production-grade code; be prepared to discuss how you manage technical debt when transitioning from prototype to scale.

Practice your answers

Technical practice

Python for Cloud-Native Applications

What to coverExplain how you structure Python applications for containerized environments. Focus on dependency management, environment variable configuration, and ensuring your code is optimized for execution within Docker containers.

CI/CD Pipeline Design

What to coverDescribe your approach to building a robust CI/CD pipeline. Discuss how you integrate automated testing, security scanning, and deployment workflows using tools like ArgoCD or similar technologies to ensure reliable software delivery.

Kubernetes and Container Orchestration

What to coverDiscuss the trade-offs between different deployment strategies in Kubernetes, such as rolling updates versus blue-green deployments. Explain how you manage resource limits and health checks to ensure application reliability.

Infrastructure as Code (IaC) Best Practices

What to coverExplain the benefits of using IaC tools like Bicep or Helm for managing cloud resources. Discuss how you maintain version control for infrastructure and ensure consistency across development, staging, and production environments.

Performance Testing and Monitoring

What to coverDescribe your methodology for performing reliability and performance testing on cloud-based applications. Explain which metrics you prioritize for application monitoring and how you use that data to identify bottlenecks.

Data Pipeline Replication

What to coverExplain the architectural considerations when building replication pipelines to connect existing solutions to new systems. Discuss how you handle data consistency, error handling, and latency in distributed environments.

Azure Cloud Services

What to coverDiscuss your experience with Azure-specific services for hosting containerized applications. Explain how you leverage Azure's managed services to simplify deployment and scaling compared to self-managed infrastructure.

Writing Maintainable Code

What to coverWhat strategies do you use to ensure code maintainability in a collaborative environment? Discuss the importance of documentation, modular design, and adhering to clean code principles when working on long-term projects.

Behavioural practice

Collaborating Across Time Zones

What to coverDescribe a situation where you had to coordinate with a distributed team across different time zones. What communication tools or processes did you implement to ensure alignment and meet project deadlines?

Handling Technical Debt

What to coverTell me about a time you identified a significant technical issue or debt in an existing platform. How did you prioritize fixing it while still delivering new features for internal customers?

Adapting to New Technologies

What to coverGive an example of a time you had to quickly learn and apply a new cloud-native tool or framework to solve a business problem. How did you approach the learning process and ensure successful implementation?

Managing Stakeholder Requirements

What to coverDescribe a scenario where you had to translate complex technical requirements into a functional prototype for an internal customer. How did you ensure the final product met their specific needs?

Sharpen your knowledge

Topics to prepare

Cloud-Native Architecture Principles
Review the core concepts of building scalable, resilient applications on cloud platforms. Focus on microservices, statelessness, and distributed system design. This is relevant to the role's requirement for building cloud-based applications on Azure and managing replication pipelines.
CI/CD Pipeline Design
Study the lifecycle of automated software delivery, including integration, testing, and deployment stages. Focus on how to ensure reliability and performance in automated workflows. This is essential for the role's responsibility to experiment with and maintain CI/CD tooling.

Skills to revise

Infrastructure as Code (IaC) with Bicep
Practice writing and deploying Azure resources using Bicep templates. Focus on modularizing infrastructure definitions to support consistent deployment workflows. This directly addresses the requirement for familiarity with Bicep and deployment automation.
Container Orchestration with Kubernetes and Helm
Create a sample application, containerize it with Docker, and define its deployment using Helm charts for a Kubernetes environment. This is critical for the role's focus on containerization and managing complex deployment workflows.
Automated Testing and Performance Monitoring
Implement unit and integration tests for a Python-based application and integrate basic application monitoring tools. This aligns with the role's mandate to perform reliability and performance testing on internal platforms.

Your preparation checklist

Demonstrate Python and Cloud-Native Proficiency
Prepare a project portfolio showcasing a Python-based application deployed on Azure using Docker and Kubernetes. Be ready to explain how you managed container orchestration and ensured the application was cloud-native.
Master Infrastructure as Code (IaC) and CI/CD Workflows
Review your experience with Bicep, Helm, and ArgoCD. Create a simple walkthrough of a CI/CD pipeline you have built or maintained, specifically highlighting how you automated testing and deployment to ensure reliable software delivery.
Prepare for System Reliability and Monitoring Discussions
Be ready to discuss your approach to performance testing and application monitoring. Prepare examples of how you have implemented process management tools to track system health and resolve bottlenecks in production environments.
Refine Cross-Functional Communication Strategies
Prepare specific examples of how you have collaborated with distributed teams across different time zones. Focus on how you communicate technical requirements and project progress to stakeholders in a global organizational structure.
Develop Targeted Questions for the AI Hub Team
Prepare thoughtful questions regarding the specific types of customer data the AI Hub processes, the current challenges in their replication pipelines, and how the team balances new feature development with maintaining existing platforms.

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