Associate Developer, Process Automation

Job Purpose and Impact

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  The Associate Developer, Automation and Cloud Engineering supports the design, development, deployment, and maintenance of automation, cloud, and AI-enabled solutions that improve operational efficiency across ERP, Manufacturing, and Supply Chain operations. This role focuses on building and supporting applications using Python, Cloud Platforms (Azure/AWS), DevOps/MLOps practices, and automation technologies while working closely with senior developers, operations teams, and DT&D partners to deliver scalable, secure, and reliable digital solutions.

  
  

Key Accountabilities

• Python Application Development: Develop, test, and maintain applications, APIs, automation scripts, and data processing solutions using Python.


• Cloud Engineering: Support deployment and management of applications and services on Azure or AWS.


• DevOps & CI/CD: Participate in source control, automated build pipelines, deployment automation, and release management.


• MLOps & AI Enablement: Support deployment, monitoring, and lifecycle management of ML and Generative AI solutions.


• Automation Development: Contribute to automation initiatives using Python, RPA tools, and workflow technologies.


• Testing & Deployment: Perform testing, support UAT, and ensure smooth production deployments.


• Post Go-Live Support: Monitor applications, resolve issues, and implement enhancements.


• Documentation & Collaboration: Maintain technical documentation and collaborate with stakeholders.

Qualifications

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  • 1–2 years of experience in Software Development, Cloud Engineering, Automation, or AI-related development
  
  
  • Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field
  
  
  • Strong programming skills in Python
  
  
  • Basic understanding of Object-Oriented Programming and software development principles
  
  
  • Hands-on exposure to Azure or AWS cloud platforms
  
  
  • Knowledge of Git, GitHub/Azure DevOps, and version control practices
  
  
  • Understanding of CI/CD pipelines and DevOps concepts
  
  
  • Knowledge of REST APIs, JSON, and integrations
  
  
  • Strong analytical and problem-solving skills
  
  
  
  

  Preferred Qualifications:

  
  
  
  
  • Exposure to DevOps/MLOps tools such as Azure DevOps, GitHub Actions, Jenkins, Docker, Kubernetes, or MLflow
  
  
  • Basic experience with Generative AI / LLM technologies
  
  
  • Experience with SQL and databases
  
  
  • Cloud certifications such as AZ-900 or AWS Cloud Practitioner