About
We have 30 years of expertise in designing and building custom software systems. We provide software development services focusing on complex high-load applications, AI and BI solutions, and mobile apps. Automating the design of chemical compounds has the potential to significantly accelerate the discovery and development of new medicines. This emerging field brings together artificial intelligence, machine learning, and established computational technologies to transform how drug discovery is approached.
Responsibilities
•Design and develop automated workflows using Apache Airflow and Python to orchestrate complex scientific and computational processes.
•Build and maintain reliable execution environments using Docker, ensuring consistent, reproducible, and scalable workflow execution.
•Integrate scientific tools, data sources, and external services through APIs and data pipelines, enabling seamless communication between different components of the research platform.
•Improve workflow reliability and scalability by monitoring execution, troubleshooting failures, optimizing processes, and collaborating with AI and scientific teams to support the development of automated drug discovery solutions.
Requirements
•Strong Python skills and hands-on experience developing automation tools, scripts, or backend components.
•Practical experience with Apache Airflow, including building, scheduling, and maintaining workflows or DAGs.
•Experience with Docker and containerized application environments.
•Understanding of software engineering best practices, including code quality, debugging, version control, and writing maintainable code.
•Ability to work with complex technical processes and collaborate effectively with engineers, data scientists, and scientific researchers.
•English level B2+.
Nice to have
•Experience with other workflow orchestration and automation platforms.
•Familiarity with AWS or other cloud environments.
•Experience querying and retrieving data from PostgreSQL and/or Snowflake.
•Knowledge of API design and integration.
•Experience with Kubernetes and container orchestration.
•Familiarity with GitOps and infrastructure or deployment automation.
•Experience developing or integrating AI-powered applications.
•An academic or professional background in life sciences, chemistry, computational biology, bioinformatics, or drug discovery.
Conditions
•Collaboration via a B2B contract with payments in USD or EUR, depending on your preference, or through a labor contract.
•Flexible work schedule.
•Possibility to work remotely.
•Opportunities for professional growth.
•A company laptop to ensure a comfortable and efficient work setup.
