Senior Python Backend Engineer - FastAPI/Django, AWS

Robotic Technologies Automation; Wilmington (DE); On-site; USD 83,000 - 103,000; Full time

Job summary

Robotic Technologies Automation in Wilmington, DE is seeking an experienced Python Developer to design, develop, and maintain scalable backend applications and services. The ideal candidate should have strong experience in Python, FastAPI, Django, REST APIs, and cloud technologies.

Responsibilities include building APIs and microservices, writing clean code, implementing asynchronous programming, troubleshooting performance, and deploying on AWS/Azure with Docker and Kubernetes.

Qualifications

• 5+ years of experience in Python development.
• Strong proficiency in Python programming and OOP concepts.
• Hands-on experience with FastAPI, Flask, or Django.
• Experience developing REST APIs and microservices.
• Strong SQL and database knowledge.
• Experience with Git, Docker, and CI/CD pipelines.
• Knowledge of AWS/Azure and Agile development methodologies.

Responsibilities

• Develop and maintain Python applications.
• Build RESTful APIs and microservices with FastAPI/Flask/Django.
• Write clean, reusable, efficient code.
• Implement asynchronous programming and integrations.
• Troubleshoot and optimize application performance.
• Work with PostgreSQL, MySQL, MongoDB, and SQL databases.
• Deploy and maintain applications on AWS or Azure.
• Use Docker, Kubernetes, and cloud-based services.

Skills

Python programming

Object-oriented programming

REST APIs

Tools

Docker

Kubernetes

Git

CI/CD pipelines

AWS

Azure

Job description

Robotic Technologies Automation in Wilmington, DE is seeking an experienced Python Developer to design, develop, and maintain scalable backend applications and services. The ideal candidate should have strong experience in Python, FastAPI, Django, REST APIs, and cloud technologies.

Responsibilities include building APIs and microservices, writing clean code, implementing asynchronous programming, troubleshooting performance, and deploying on AWS/Azure with Docker and Kubernetes.