About Wajdi
- Are launching a new project in the cloud
- Are migrating existing applications to the cloud
- Are looking to enhance the stability/reliability of your cloud-based applications
French
Native or bilingual
English
Native or bilingual
Experience
- RenaultLead Cloud DevOps & MLOpsAUTOMOBILEJanuary 2022 - Today (4 years and 7 months)Boulogne-Billancourt, FranceAs an Agentic AI Architect & DevOps Engineer, I design, industrialize, and secure cloud platforms for deploying data, AI, and agentic systems on Google Cloud Platform. I am involved in the entire lifecycle: architecture, CI/CD automation, infrastructure as code, observability, security, and supporting development teams.
- Design the technical architecture and industrialization pipelines for deploying AI applications and agentic services in secure and scalable cloud environments.
- Set up and maintain CI/CD pipelines with GitLab CI and Cloud Build, covering validation, testing, build, deployment, and cross-environment promotion phases.
- Automate Python and Terraform code quality checks with pylint, mypy, black, terraform fmt, as well as integrated validation and security tools within the pipelines.
- Execute and industrialize unit, functional, and integration tests to reduce regression risks and ensure reliable production deployments.
- Build Docker images with Kaniko and generate necessary execution artifacts for service deployment: configurations, binaries, and manifests.
- Perform code reviews, approve pull requests, and promote good development practices: separation of concerns, test coverage, maintainability, and code readability.
- Refactor technical components to improve their modularity, robustness, and scalability.
- Support developers in adopting DevOps, GitOps, and Infrastructure as Code practices, particularly for the industrialization of AI services.
- Autobiz (Groupe Stellantis)Data & AI Platform Architect (GCP)AUTOMOBILEApril 2022 - December 2024 (2 years and 9 months)Courbevoie, FranceAs part of the company's cloud transformation, I designed and industrialized a data platform on GCP to host analytical, AI, and agentic workloads. The objective was to provide a secure, scalable, and observable cloud foundation for integrating internal data, orchestrating processing, and preparing for the deployment of generative AI and intelligent agent solutions.The mission also covered:
- Preparing the data architecture necessary for feeding AI systems and conversational or operational agents.
- Designing secure data access patterns for AI applications: access control, identity management, network segmentation, and traceability.
- Implementing reusable orchestration and monitoring mechanisms for data processing and future agentic workflows.
- Defining CI/CD and GitOps standards for industrializing the deployment of data components, microservices, and AI applications.
- Implementing the observability foundations required for monitoring the performance, errors, costs, and availability of AI workloads.
- SERVIER MONDELead Data EngineerPHARMACEUTICALS INDUSTRYOctober 2020 - March 2022 (1 year and 6 months)Paris, France2 projects:ETL pipeline creation tool (Python, Apache Beam & Dataflow) for medical data.Design, build & deploy of a data analysis environmentPROJECT 1Design, build & deploy of a data analysis environment on the group's cloud platform for centralizing clinical study processing:➔ High availability storage of datasets (GCS)➔ Setup of a data catalog system (Fast API)➔ Permissions and authorization management➔ IaC for resource management (GCS Buckets, Service Accounts, GKE, BigQuery Datasets) with TerraformPROJECT 2On the group's Data Platform (Google Cloud Platform):➔ Implementation of ETL pipelines (Python, Apache Beam & Dataflow) for medical data from external databases.➔ Creation of a graph (Neo4j) linking different elements retrieved through ETL pipelines (treatments, scientific publications, diseases, genes, etc.)➔ Setup of CI/CD pipelines (Cloudbuild)➔ Automation/Scheduling of ingestion and ETL jobs (Argo Workflow)➔ Database maintenance (ElasticSearch and Neo4j deployed on Kubernetes)➔ IaC for resource management (GCS Buckets, Service Accounts, GKE, BigQuery Datasets) with Terraform
Reviews
Recommendations
These freelancer profiles also match your criteria
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Education
- Polytechnic EngineerEcole Polytechnique de Tunisie2014