About the Role:

We are seeking a highly skilled and innovative Python Full Stack Developer to join our engineering team. This role requires a strong foundation in full stack development with a focus on cloud-native applications and AI integration. You will play a critical role in building scalable web solutions, integrating machine learning models, and working closely with data scientists and DevOps teams to bring intelligent services to production.

Key Responsibilities:

• Develop and maintain scalable and responsive web applications using Python (Flask, Django, or FastAPI) and ReactJS.
• Design, build, and maintain RESTful APIs and microservices to support AI-driven applications.
• Deploy and integrate machine learning models and data pipelines into production environments.
• Utilize AWS cloud services (Lambda, S3, EC2, API Gateway, SageMaker, etc.) for cloud-native application development.
• Collaborate with cross-functional teams including data scientists, DevOps engineers, and product managers to deliver AI-powered features.
• Optimize applications for performance, scalability, and security.
• Participate in agile ceremonies, perform code reviews, and contribute to continuous improvement initiatives.

Required Skills:

• Strong proficiency in Python and JavaScript (ReactJS preferred).
• In-depth knowledge of backend frameworks such as Django, Flask, or FastAPI.
• Hands-on experience with cloud-native development using AWS.
• Good understanding of AI/ML workflows and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Proficiency in containerization tools (Docker, Kubernetes) and experience with CI/CD pipelines.
• Solid knowledge of application performance, scalability, and security best practices.
• Excellent communication skills and the ability to collaborate effectively in a team environment.

Preferred Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Exposure to MLOps tools and practices (e.g., MLflow, SageMaker Pipelines).
• Experience with data visualization tools and BI platforms.
• Understanding of data engineering concepts such as ETL, data lakes, and real-time data streaming.