Senior Python Developer

Requirements

• 7+ years of experience in backend software development with a focus on building scalable and maintainable solutions.
• Strong programming skills in Python, with a deep understanding of writing clean, efficient, and well-structured code.
• Experience with web frameworks, including FastAPI and developing RESTful APIs.
• Proficiency in version control using Git and maintaining structured pull requests.
• Test-Driven Development (TDD) experience: writing unit tests with Pytest and implementing integration tests to ensure robustness and reliability.
• Experience with CI/CD pipelines and automated deployment practices.
• Familiarity with DevOps concepts, including containerization (e.g., Docker), orchestration (e.g., Kubernetes), and cloud infrastructure management (AWS, Azure, GCP).
• Experience in data engineering within Big Data ecosystems, including data pipelines and data integration.
• Knowledge of fundamental computer science concepts, including data structures, algorithms, and problem-solving.
• Excellent communication skills and ability to work collaboratively within cross-functional teams.
• Proficiency in English, both written and spoken.
• Asynchronous programming skills
• Architectural thinking: be able to design services.
• Good OOP and design patterns knowledge.
• Experience with OOP languages: C++, C# or Java.
• SQLAlchemy experience.

Nice to have 

• Experience with Machine Learning (ML): deploying and managing models, creating inference pipelines, and ML Ops practices.
• Knowledge of ML platforms such as Airflow, SageMaker, Kubeflow, or MLFlow.
• Experience with distributed computing (e.g., Spark/PySpark).
• Understanding of cloud ML deployment and model serving on platforms like AWS, Azure, or GCP.
• Experience with Large Language Models (LLMs), model fine-tuning, and Retrieval-Augmented Generation (RAG) pipelines.

Responsibilities

• Develop, maintain, and optimize backend services and APIs using Python, ensuring high performance and scalability.
• Design and implement data processing pipelines to handle large volumes of data efficiently.
• Collaborate with cross-functional teams to understand client needs and translate them into practical features.
• Write clean, testable, and maintainable code, following best practices and coding standards.
• Ensure code quality through code reviews, unit testing (using Pytest), and integration testing.
• Implement and maintain CI/CD pipelines, and ensure smooth deployment processes.
• Integrate and manage cloud-based solutions and infrastructure (e.g., AWS, Azure, GCP).
• Utilize DevOps tools and practices for containerization and orchestration (Docker, Kubernetes).
• Monitor application performance, identify bottlenecks, and implement improvements.
• Participate in team meetings, providing updates on progress and discussing upcoming tasks.
• Utilize issue tracking and version control systems (like Git) to maintain high-quality software development processes.
• Stay updated on the latest technologies and apply innovative solutions where applicable.

Nice-to-Have Responsibilities (ML Focus):

• Develop, refine, and utilize ML engineering platforms and components as needed.
• Establish and manage processes for data preparation, feature engineering, and prediction.
• Closely monitor model performance and address any issues that arise.
• Explore opportunities to integrate ML workflows into backend systems when it adds value.