Must have

• Python

• FastAPI

• SQL

• Flask

• NoSQL

• CD

• Cloud

• Polish (B2)

• English (B2)

Nice to have

• Java

• C#

• C++

• PyTorch

• scikit-learn

Requirements description

What you will need:

• At least 6 years of experience and fluency in Python development ecosystem,
• Experience in building back-end services in Python with frameworks like FastAPI (or Flask), SQL and NoSQL databases,
• Knowledge of clean code and design patterns in Python, strong attitude to build well structured, high quality solutions,
• Experience in writing robust unit tests for developed applications,
• Experience in u sing GenAI models in building business applications,
• Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-native technologies,
• Familiarity with Continuous Deployment lifecycle,
• Excellent problem-solving and analytical skills,
• Ability to work independently and as part of a team,
• Very good knowledge of English and Polish
• Strong communication and documentation skills

Nice to have:

• Knowledge of another object-oriented programming language (Java/C#/C++)
• Knowledge of Machine Learning algorithms and libraries (scikit-learn, PyTorch)

Offer description

C&F is a technology services company providing innovative solutions in Data Management, Big Data, Advanced Analytics and Compliance. With a highly integrated team of 400+ experts, for over 20 years C&F has been delivering superior engineering and premium operations to Fortune 500 companies, primarily in the Life Science industry.

As a Senior Python Developer you’ll design and build GenAI solutions and backend components in Python, collaborate with data and ML teams, and integrate AI models into scalable applications. The role requires strong Python expertise, experience with cloud platforms (AWS/Azure/GCP), and knowledge of modern backend frameworks and best coding practices.

Your responsibilities

1. Design architecture of GenAI applications,
2. Design, develop, and maintain Python code in AI applications and components,
3. Code review and identification of areas of improvments,
4. Collaborate with data scientists and machine learning engineers to utilize AI models in the applications,
5. Knowledge of basic types of solutions using GenAI models (RAGs, agentic workflows, etc.)
6. Collaborate with other roles (managers, testers, DevOps, etc.) through the whole life cycle of a project,

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