Freelancer profile translated to English.

Description

Software Engineer / Tech Lead Python (~11 years) specializing in backend, Azure Cloud, and DevOps, with a strong DevSecOps focus: vulnerability monitoring, secrets management, code quality and security, observability. Experienced in taking over existing solutions (PoCs) and industrializing them on Kubernetes.

Recent experience in agentic AI systems (LLM agents, tool-use / function-calling, MCP, RAG) applied to operations, detection, and automation.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent
Arabic
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

SFR
Python Development Engineer
TELECOMMUNICATIONS
September 2023 - Today (2 years and 11 months)
As part of the critical application management at SFR, I contributed to the development of an alarm management system, aiming to centralize and automate incident management from various sources (Prometheus, Shenken, Vtom, etc.) to improve responsiveness and reduce manual interventions.

Missions and Achievements:

- Python Engine Development: Real-time alarm centralization via Kafka and data processing before storage in MongoDB.

- Asynchronous Microservices: Designed with FastAPI and asyncio for incident ticket management and corrective task automation.

- Concurrency Management: Used semaphores to manage concurrency in microservices.

- Monitoring Interface: Created a Grafana dashboard for real-time visualization of service status.

- Automatic Remediation: Implemented remediation mechanisms in Airflow to create tickets or escalate in case of critical incidents.

- Orchestration and Deployment: Deployed microservices with Kubernetes and Helm, managed CI/CD pipelines with GitLab.

- Log Automation: Set up the ELK Stack via Ansible for automated log management.

- Collect data from various sources and model this data to simplify visualization and analysis.

- Complex Workflow Management: Developed data extraction processes via Airflow to reliably manage workflows.

Technical Environment:

Languages/Frameworks: Python, FastAPI, asyncio, SvelteKit
Databases: MongoDB
Monitoring/Visualization Tools: Grafana, Prometheus, Kibana
Orchestration/Containerization: Kubernetes, Helm, Docker
Automation/CI/CD: Ansible, GitLab CI
Data Streams: Kafka
Scheduling/Remediation: Airflow
FastAPI asyncio Kubernetes Docker Airflow Ansible Gitlab CI/CD Apache Kafka Logstash Elastic Stack (ELK) Grafana Prometheus REST APIs Observability
BNP PARIBAS
Python Development Engineer / Data
BANKING AND INSURANCE
March 2022 - September 2023 (1 year and 6 months)
Paris, France
Context:
Development of a centralized solution to monitor and reduce vulnerabilities by consolidating data from servers and workstations, with a natural language search interface and advanced visualizations.

Key Achievements:

Data Collection and Processing:
- Developed a custom Python engine to extract data from SQL Server and RESTful APIs.

- Optimized SQL queries and Elasticsearch indexing for performance improvement.

- Automated daily Elasticsearch index updates with asynchronous processing via asyncio and aiohttp.

API Development and AI Integration:
- Created secure APIs with FastAPI to expose consolidated data.
Integrated OpenAI API for intelligent natural language search.

Frontend Development and Visualization:
- Interactive interface with Streamlit for intelligent searches.
Advanced dashboards with Kibana for predictive analytics.

Data Archiving and Storage:
- Automated archiving to AWS S3 with multithreading management.
Observability and Monitoring:
- Implemented monitoring systems with Prometheus, Grafana, ELK, and Nagios.

Code Quality and Collaboration:
- Applied coding standards (Black, Pylint, Bandit) and regular code reviews.
Documentation:

Wrote detailed guides on data collection, processing, and exposure flows.

Technical Environment:
Python, FastAPI, OpenAI API, Elasticsearch, SQLAlchemy, Streamlit, Pandas, Ansible, AWS S3, Kibana, Nagios, Prometheus, SQL Server, Red Hat, Windows, Git, Bitbucket, VSCode, Jira.

Methodology: Agile Scrum
Python 3 FastAPI Elastic Stack (ELK) PostgreSQL OpenAI Streamlit SQLAlchemy AWS S3 Prometheus Pandas
Direction générale des finances publiques
DGFIP
PUBLIC SECTOR
July 2018 - May 2020 (1 year and 10 months)
Paris, France
Context:
Contribution to the development of a tool to automate the generation of configuration files for setting up various platforms for government ministries.

Key Achievements and Responsibilities:

Configuration File Automation
- Designed and automated the generation of YAML files for seamless integration with Puppet, simplifying configuration management on servers.

Development and Validation
- Created and executed functional tests with Selenium, ensuring application requirements compliance and optimal user experience.

- Developed database fixtures with Django ORM to interact with PostgreSQL, facilitating the creation of a reliable test environment.

- Implemented unit tests with Unittest to ensure robust code coverage and early bug detection.

Collaboration and Quality
- Collaborated closely with project architects to identify and fix bugs, improving application quality and performance.
Deployment and Orchestration

- Integrated and used OpenShift to orchestrate and deploy generated platforms, ensuring optimal container and application management in a hybrid cloud environment.

CI/CD Automation

- Set up and maintained a CI/CD pipeline with GitLab CI, automating testing and deployment processes for fast and reliable delivery.

Technical Environment:
Technologies: Python, Django Framework, Django Rest Framework, Selenium, PostgreSQL, JSON, OpenShift.

Tools: Git, GitLab CI, flake8, Unittest, coverage, Puppet.
Python/Django Puppet GitlabCI Unit Test docker-compose REST API