About Company

A well-established IT services and digital transformation company with over two decades of industry presence is expanding its team. The organization delivers enterprise software solutions, cloud platforms, AI-driven applications, and secure technology services to global clients across multiple domains. With a strong technical workforce and globally recognized quality and security standards, the company offers a stable environment focused on long-term growth, innovation, and high delivery excellence.

Technical Skills:

Programming: Python, TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, MCP Servers.

Version Control: Git, GitHub, Bitbucket.

Databases: SQL, NoSQL, PostgreSQL, MongoDB, Cosmos Db

CI/CD: Jenkins, GitLab CI, CircleCI, Travis CI.

Containerization: Docker, Kubernetes, OpenShift.

Microservices: RESTful APIs, Flask, Django, FastAPI.

Monitoring: Prometheus, Grafana, ELK stack, Splunk

Security: OWASP, SSL/TLS, IAM.

Agile Tools: Jira, Trello, Confluence.

Testing: PyTest, UnitTest, Selenium.

Cloud: GCP, Azure, AWS

Responsibilities:

Additional Responsibilities:

AI Integration: Seamlessly integrate AI models into applications using TensorFlow and PyTorch.

API Development: Develop and maintain APIs using Flask and Django.

Data Pipelines: Build and maintain efficient data pipelines using Pandas and NumPy.

Validation: Ensure data quality and consistency using PyTest and UnitTest.

Scalability: Design systems for optimal performance using Kubernetes and Terraform.

Automation: Automate deployment processes using Jenkins and GitLab CI.

Monitoring: Set up monitoring and logging using Prometheus, Grafana, and ELK stack.

Security: Implement security best practices using OWASP guidelines and IAM.

Testing: Implement automated testing frameworks using Selenium and PyTest.

Feedback: Incorporate user feedback for continuous improvement using agile methodologies.

Requirements:

Education: Bachelor's or master’s in computer science or related field.

Experience: 3-6 years in software development and pipeline engineering.

Technical Proficiency: Strong Python skills; experience with TensorFlow, PyTorch, Keras.

Cloud Platforms: Familiarity with AWS, Google Cloud, Azure.

Deployment: Experience with Docker, Kubernetes, CI/CD tools (Jenkins, GitLab CI, CircleCI).