Python Full Stack Engineer
The Smart
United States
2 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Working hours
Regular working hours
Job source
Tech stack
Clean Code Principles
Multitier Architecture
Artificial Intelligence
Application Integration Architecture
Application Performance Management
Application Services
User Authentication
Automation of Tests
Microsoft Azure
Cloud Computing
Software Quality
Code Review
+32 more
Computer Programming
Databases
Data Integration
DevOps
Middleware
Github
Python (Programming Language)
Key Management
Routing
NoSQL
Platform as a Service (PAAS)
Performance Tuning
Search Technologies
Software Construction
Software Deployment
Software Engineering
Web Applications
Data Logging
Feature Engineering
ReactJS
Large Language Models
Prompt Engineering
Generative AI
Backend
Git
Fastapi
Integration Tests
Information Technology
Celery
Front End Software Development
Restful APIs
Serverless Computing
Job description
The Python Full Stack Engineer designs, builds, and maintains production-grade web applications end-to-end. This role focuses on developing FastAPI backends, React frontends, and deploying applications on Azure App Services using GitHub CI/CD pipelines. Additionally, the engineer integrates practical AI capabilities-including Azure OpenAI, Azure AI Foundry, LangChain, and prompt engineering-to ship robust features such as Retrieval-Augmented Generation (RAG), smart assistants, and automated tools., Backend & Frontend Engineering
- Design, build, and maintain scalable backend services and REST APIs in Python using FastAPI, middleware, background tasks, and database integrations.
- Develop and maintain performant, user-friendly, and testable frontend interfaces using React, modern state management, and hooks.
- Apply software engineering best practices, including unit/integration testing, clean architecture, documentation, logging, and performance optimization.
Cloud, DevOps, & Observability
- Deploy, operate, and troubleshoot full-stack web applications on Azure App Services, managing configuration, scaling, and incident response.
- Build and manage automated CI/CD pipelines on GitHub, incorporating automated testing, code quality checks, and deployments.
- Securely integrate core Azure services, including Azure Key Vault, Azure Storage, and Application Insights for observability and monitoring.
AI Integration & Feature Engineering
- Implement practical AI-powered features, smart tools, and assistants using Azure OpenAI and Azure AI Foundry.
- Utilize LangChain or similar frameworks to orchestrate LLM workflows, tools, agents, and Retrieval-Augmented Generation (RAG) patterns.
- Apply structured prompt engineering techniques to ensure reliability, safety, quality, and mitigation of LLM hallucinations.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 4 or more years of professional software engineering experience building and operating production systems.
- Strong Python development capabilities, including typing, packaging, async programming, and clean code organization.
- Solid experience building backend APIs with FastAPI (or similar frameworks), including routing, middleware, authentication, and async I/O.
- Hands-on frontend development experience using React (hooks, state management, API integration, and testing fundamentals).
- Experience deploying and running web applications on Azure App Services or similar PaaS environments.
- Proficiency with Git, GitHub Actions, pull requests, code reviews, and CI/CD pipelines.
- Familiarity with relational or NoSQL database integration within Python backends., * Hands-on experience integrating LLMs using Azure OpenAI, Azure AI Foundry, and vector search services (e.g., Azure AI Search).
- Exposure to LangChain or similar frameworks for building LLM workflows, tool-using agents, and RAG architectures.
- Working knowledge of prompt engineering patterns (system prompts, few-shot prompting, structured outputs, and safety guardrails).
- Experience with background task processing frameworks (e.g., Celery, RQ, Azure Functions, or queue systems).
- Experience establishing observability stacks (logging, metrics, tracing) within Azure environments.
- Prior experience in client-facing or consulting technology environments., * Application-first engineering mindset prioritizing clean architecture, maintainability, reliability, and code quality.
- Strong analytical and problem-solving skills to own features end-to-end from technical design through deployment and monitoring.
- Excellent communication and collaborative skills to partner effectively with product, design, and engineering teams.
- Practical approach to evaluating and applying emerging AI capabilities within production software limits.
Benefits & conditions
- Competitive salary
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