SENIOR PYTHON DEVELOPER (IR-446)

Intellectsoft is a software development company delivering innovative solutions since .
We operate across North America, Latin America, the Nordic region, the UK, and Europe.
e specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive growth and scalability.
Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, Qualcomm, and London Stock Exchange.
ogether, our team delivers solutions that make a difference.
Learn more at www.
ntellectsoft.
et Our customer's product is an AI-powered platform that helps businesses make better decisions and work more efficiently.
It uses advanced analytics and machine learning to analyze large amounts of data and provide useful insights and predictions.
The platform is widely used in various industries, including healthcare, to optimize processes, improve customer experiences, and support innovation.
It integrates easily with existing systems, making it easier for teams to make quick, data-driven decisions to deliver cutting-edge solutions.
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.
., Docker), orchestration (e.
., Kubernetes), and cloud infrastructure management (AWS, Azure, GCP).
Experience in data engineering within Big Data ecosystems, including data pipelines and data integration.
Solid understanding of software architecture and system design for high-availability applications.
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.
Nice to have skills 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.
., 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.
Experience in developing enterprise-grade applications that leverage data-driven decision-making.
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.
., 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.
Stay informed about ML Ops practices and maintain pipelines for training and inference.
35 absence days per year for work-life balance Udemy courses of your choice English courses with native-speaker Regular soft-skills trainings Excellence Сenters meetups Online/offline team-buildings