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Senior Python Developer

SYSTEM SOFT TECHNOLOGIES LLCUnited States🇺🇸United StatesPosted Sep 12, 2026

Why This Role Stands Out

This hybrid Senior Python Developer role at SYSTEM SOFT TECHNOLOGIES LLC offers a fantastic opportunity to advance your career with a reputable company and develop your skills across various technologies. You'll thrive here if you're a proactive problem-solver with a strong foundation in Python and a desire to contribute to impactful projects, so be sure to apply!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
6 days ago
DjangoDockerFastAPIFlaskMongoDBMySQLAWSMachine LearningNumPyScikit-learnAzureGitGoogle CloudKubernetesPandasPostgreSQLPython

Job Description

Python Developer (Remote)

We are Open for sponsorship someone who can work on our W2 Required Qualifications & Skills

  • Experience: 3+ years of professional experience as a Python Developer, Software Engineer, or in a strictly related backend role.

  • Core Python: Deep understanding of Python syntax, standard libraries, and object-oriented programming (OOP) principles.

  • Frameworks: Hands-on experience developing with major Python web frameworks such as Django, Flask, or FastAPI.

  • Databases & ORM: Strong command of relational databases (e.g., PostgreSQL, MySQL), Object-Relational Mapping (ORM) tools like SQLAlchemy, and basic knowledge of NoSQL databases (e.g., MongoDB).

  • Version Control: Proficiency in utilizing Git and collaborative platforms like GitHub, GitLab, or Bitbucket.

  • Soft Skills: Strong analytical thinking, excellent problem-solving capabilities, and a team-first communication style.

Preferred Qualifications (Bonus Skills)

  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field.

  • Experience with cloud hosting and infrastructure platforms (AWS, Google Cloud, Azure).

  • Familiarity with containerization and orchestration technologies like Docker and Kubernetes.

  • Understanding of Continuous Integration/Continuous Deployment (CI/CD) pipelines.

  • Exposure to data engineering, automation, or machine learning libraries (e.g., Pandas, NumPy, Scikit-Learn).

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