Software Engineer

RESPONSIBILITIES
Lead the design, development, and deployment of Python-based cloud infrastructure management and automation solutions.
Architect and deploy scalable infrastructure as code (IaC) using tools like Terraform and Azure DevOps.
Integrate AI/ML technologies via API to automate cloud operations such as reporting, orchestration, resource provisioning, scaling, monitoring, and optimization.
Collaborate with solution architects and devops engineers to translate requirements into programming specifications to build AI-driven automation pipelines for cloud management and reporting tasks.
Oversee the development and deployment of AI models in production environments for predictive analytics related to cloud resource management and reporting using Python, leveraging advanced techniques with LLMs, RAG, and Prompt Engineering to solve complex problems and explore new approaches.
Implement version control and continuous integration/continuous deployment (CI/CD) pipelines for automated testing, deployment, and monitoring of cloud applications.
Mentor junior engineers and provide technical leadership in Python development, cloud architecture, and automation best practices.
Oversee and conduct code reviews on python-based automation developed by other team members to ensure high-quality, maintainable code that adheres to best practices.
Ensure security and data protection measures are implemented.
Stay up to date with industry trends and emerging technologies relevant to Python development, AI/ML, cloud computing, and API integrations.
Document development processes, code changes, and best practices for future reference and training purposes.
Experience & SKILLS REQUIRED
5+ years of experience in Python development with a strong focus on cloud automation. Proficiency in writing clean, efficient, and scalable Python code is crucial. This includes a deep understanding of Python libraries and frameworks as well as proven experience in developing Web APIs using Python.
Proficiency with Python frameworks like Django or Flask.
Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar.
Extensive experience with AWS (e.g., EC2, Lambda, S3) and Azure (e.g., App Service, Azure Functions) services.
Strong proficiency in infrastructure as code (IaC) tools such as Terraform for automating cloud deployments.
Experience with integrating AI/ML technologies into cloud management workflows (e.g., predictive scaling, anomaly detection).
Knowledge of containerization technologies like Docker and orchestration platforms like Kubernetes.
Strong experience with API design, RESTful services, and integrating third-party APIs for automation purposes.
Solid understanding of software development best practices including version control (Git), testing, and continuous integration tools (e.g., Azure DevOps).
Strong understanding of security best practices in cloud environments, including IAM policies and encryption strategies.
Experience with serverless architectures (e.g., AWS Lambda, Azure Functions).
Familiarity with monitoring tools such as Prometheus or Datadog for AI-driven anomaly detection.
Proficiency in software design patterns, architectural principles, and best practices to create robust and scalable software solutions.
Proficiency in guiding developers on SDK consumption and best practices.
Understanding of AI technologies and practical experience with LLMs, RAG, and Prompt Engineering.
Familiarity with machine learning frameworks and libraries, as well as experience in data analysis and manipulation.
Familiarity with Agile methodologies for project management.
Excellent problem-solving skills with attention to detail.
Strong communication skills and ability to work in a collaborative environment.
EDUCATION
Bachelor’s degree in computer science, Information Systems, or a related field, or equivalent experience.
Travel requirements