Technology

Senior Python Developer

SYSTEM SOFT TECHNOLOGIES LLCUnited States🇺🇸United StatesPosted Oct 2, 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

1 week 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).