About this role
Job Purpose and Impact 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 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