Associate Software Engineer

• Design and Development: Architect, develop, and maintain scalable and efficient software solutions using Python and its frameworks (e.g., Django, Flask, FastAPI).
• Cloud Integration: Build and deploy cloud-native applications on platforms such as AWS, Azure, or Google Cloud, leveraging services like serverless computing, containerization (Docker, Kubernetes), and cloud storage.
• Code Quality: Write clean, maintainable, and testable code while adhering to best practices in software development.
• Collaboration: Work closely with cross-functional teams, including product managers, DevOps engineers, and data scientists, to deliver end-to-end solutions.
• Performance Optimization: Identify bottlenecks and optimize application performance, ensuring high availability and reliability.
• Mentorship: Provide technical guidance and mentorship to junior engineers, fostering a culture of continuous learning and improvement.
• Security and Compliance: Ensure that all software solutions comply with security standards and industry regulations.
• Monitoring and Maintenance: Implement monitoring tools and processes to ensure the health and performance of applications in production environments.

• Bachelor’s, Master’s, Computer Science, or a related field.
• 8+ years of professional experience in software development, with a focus on Python and cloud technologies.
• Expert in Python and its frameworks (e.g., Django, Flask, FastAPI) and proficiency with other languages such as C++/Rust
• Strong understanding of cloud platforms (AWS, Azure, Google Cloud) and their services, including serverless architectures, container orchestration (Kubernetes), and CI/CD pipelines.
• Experience with database systems (SQL and NoSQL) and data processing tools.
• Familiarity with microservices architecture and RESTful API design.
• Proven track record of delivering scalable and reliable software solutions in production environments.
• Solid foundation on data structure and algorithms
• Knowledge of DevOps principles and CI/CD pipelines for automated testing and deployment.

• Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Google Cloud Professional Engineer).
• Knowledge of DevOps practices, including infrastructure as code (e.g., Terraform, Ansible).

• Familiarity with AI/ML concepts, such as machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), or natural language processing.
• Experience working with AI/ML pipelines, model deployment, or data preparation workflows.
• Interest in contributing to AI/ML-related projects or collaborating with data scientists and machine learning engineers.

• India – (Flexible hybrid work model - work from Bangalore office for 20 days in a quarter)

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