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.
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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
