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BACKEND

🐍 Python

Production-grade Python backends from an engineer who's shipped at scale

8+ Years Experience
40+ Projects Delivered
✓ Available for new projects
Used at:
Anaqua Flowrite Pipelinepharma ActivePrime Crowdbotics PurpleSlate Spiio

$ cat services.json

Backend System Development

Build complete Python backend systems from architecture to deployment.

Deliverables:
  • System architecture design
  • API development (REST, GraphQL)
  • Database design and optimization
  • Authentication and authorization
  • Testing and CI/CD setup

AI/ML Backend Integration

Integrate machine learning models and LLMs into production systems.

Deliverables:
  • Model serving infrastructure
  • Feature pipelines
  • LLM integration (OpenAI, Anthropic)
  • Vector database setup
  • Cost optimization

Legacy Modernization

Upgrade and modernize existing Python codebases.

Deliverables:
  • Python 2 to 3 migration
  • Sync to async conversion
  • Framework upgrades
  • Performance optimization
  • Technical debt reduction

$ man python

My Python Framework Experience

I’ve built production systems with every major Python framework:

FastAPI - My choice for new AI/ML projects

  • Async-first, perfect for I/O-bound LLM calls
  • Auto-generated OpenAPI documentation
  • Pydantic for bulletproof validation

Django - Enterprise-grade web applications

  • Django REST Framework for APIs
  • Admin interface for internal tools
  • Battle-tested security

Flask - Lightweight microservices

  • Simple and flexible
  • Great for small services
  • Easy to extend

Production Python Best Practices

Every Python project I deliver follows these standards:

  • Type Hints - Full typing with mypy validation
  • Testing - pytest with 80%+ coverage target
  • Linting - ruff, black, isort for consistency
  • Async - Proper async patterns when beneficial
  • Logging - Structured logging with correlation
  • Error Handling - Comprehensive exception hierarchy
  • Documentation - Docstrings and API docs

$ cat README.md

Why Python for Backend Development?

Python has become the language of choice for backend development, especially in AI/ML-heavy applications:

  • AI/ML Ecosystem: TensorFlow, PyTorch, LangChain—all Python-first
  • Developer Productivity: Rapid development without sacrificing quality
  • Mature Frameworks: Django, FastAPI, Flask—battle-tested options
  • Community: Massive ecosystem of libraries and tools

My Python Stack

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# Frameworks
FastAPI      # High-performance async APIs
Django       # Full-featured web applications
Flask        # Lightweight microservices
Celery       # Distributed task processing

# Data & Databases
SQLAlchemy   # ORM with async support
Alembic      # Database migrations
Pydantic     # Data validation
pandas       # Data processing

# AI/ML
LangChain    # LLM orchestration
OpenAI       # GPT integration
Anthropic    # Claude integration
HuggingFace  # Open source models

# Testing & Quality
pytest       # Testing framework
mypy         # Static type checking
ruff         # Fast linting
black        # Code formatting

# Deployment
Docker       # Containerization
Gunicorn     # WSGI server
Uvicorn      # ASGI server

Python Project Structure I Use

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project/
├── src/
│   ├── api/           # FastAPI routes
│   ├── core/          # Business logic
│   ├── models/        # Pydantic/SQLAlchemy models
│   ├── services/      # External integrations
│   └── utils/         # Shared utilities
├── tests/
│   ├── unit/
│   ├── integration/
│   └── conftest.py
├── alembic/           # Migrations
├── docker/
├── pyproject.toml     # Dependencies
└── README.md

Industries I’ve Served with Python

  • LegalTech: IP management, contract analysis
  • SaaS: Email automation, CRM integrations
  • AgriTech: IoT data processing, sensor analytics
  • FinTech: Transaction processing, compliance
  • HealthTech: Hospital management, patient systems

Experience:

Related Services: Django, FastAPI, Flask, Celery, LangChain

$ ls -la projects/

Enterprise AI Backend

@ Anaqua
Challenge:

Build unified Python backend for all AI features across IP management platform.

Solution:

Designed FastAPI-based microservices with shared AI primitives, standardized patterns, and comprehensive monitoring.

Result:

Became the foundation for the company's AI transformation.

CRM Data Integration Platform

@ ActivePrime
Challenge:

Maintain and enhance integrations across Salesforce, Dynamics 365, Oracle, and more.

Solution:

Built Flask-based Python services with robust error handling, retry logic, and comprehensive testing.

Result:

Improved reliability and reduced integration failures.

AI Recruitment Platform

@ Crowdbotics (RecruitBot)
Challenge:

Build backend for AI-powered recruitment matching 600M+ candidate profiles.

Solution:

Django REST Framework with optimized database queries, Scala microservices for performance-critical paths.

Result:

Enabled 60% reduction in time-to-fill for clients.

$ diff me competitors/

+ 8+ years of Python—not just syntax, but idioms and best practices
+ Async Python expert—proper handling of concurrent operations
+ AI/ML integration specialist—built production LLM systems
+ Full-stack Python—from scripts to enterprise applications
+ Clean code advocate—maintainable systems that scale

Discuss Your Python Project

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