Technology and Responsibilities :

- Experience in GenAI project [Good to have]

- Programming Languages

- Python (Django, Flask)

- Frameworks

- Django / Flask (Python)

- Express.js (Node.js)

- Databases

- Relational: MySQL, PostgreSQL, Oracle

- NoSQL: MongoDB, Redis, Cassandra

- Server, Hosting & Deployment

- Docker & Kubernetes

- CI/CD tools (Jenkins, GitHub Actions)

- Cloud platforms (AWS, Azure, GCP)

- Security

- Authentication & Authorization (OAuth, JWT)

- Data validation & sanitization

- Version Control

- Git (GitHub, GitLab, Bitbucket)

- API & Microservices Development - Design scalable RESTful APIs services. Secure AI endpoints using OAuth2, JWT authentication, and API rate limiting.

- Lead the design, development, and optimization of complex Python applications and systems.

- Architect scalable and secure backend solutions, ensuring best practices in coding and design.

- Guide junior developers through mentoring, code reviews, and technical leadership.

- Collaborate with product owners, architects, and stakeholders to translate business requirements into
technical solutions.

- Ensure system performance, reliability, and scalability through monitoring and optimization.

- Contribute to setting coding standards, best practices, and development processes.

- Drive automation, CI/CD integration, and DevOps practices in Python development.

Qualifications we seek in you :

Minimum Qualifications :

- Python Programming: Proficiency in Python programming language.

- Knowledge of PL/SQL programming language and Oracle database concepts.

- Experience with integrating Python applications with Oracle databases using PL/SQL.

- Understanding of data analysis concepts and experience with data visualization tools.

- Strong problem-solving skills and ability to debug code.

Preferred Skills :

- Experience with big data frameworks (PySpark, Dask) or data pipelines (Airflow, Luigi).

- Knowledge of DevOps practices and tools (Jenkins, GitHub Actions, Terraform).

- Familiarity with security practices in Python application development.

- Exposure to machine learning libraries (scikit-learn, TensorFlow, PyTorch) for AI-driven applications.

- Leadership in designing enterprise-grade applications and managing development teams