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Wajdi FarhaniWF

Wajdi Farhani

Supermalter

Cloud & AI Architect • Certified GCP Architect

€750/day
2 projects
Paris, FR
8-15 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Wajdi

DevOps & Data/Cloud Architecture Engineer with 12 years of experience in designing, implementing, and optimizing robust and highly available cloud infrastructures.

Specialized in Cloud Data Management, Application Lifecycle (CI/CD), and migration to modern architectures.

Solid expertise in Google Cloud Platform, with a mastery of Infrastructure as Code (IaC) practices (Terraform, Ansible).

I can assist you if you:
  • 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
I support my clients in structuring/exploiting their data in the cloud (GCP, AWS, etc.) with two objectives: maximizing infrastructure reliability and optimizing operational costs while respecting functional guidelines (business requirements).

10+ years of experience during which I have supported20+ clients(Large corporations, Startups & SMEs) in theimplementation of their cloud data platforms and themigration of their workloads to the cloud: Databases, APIs, Web Applications, etc.

Specifically, my expertise will be useful if:

➡️ you are looking toleverage GCP/AWS cloud platforms at a lower cost,
➡️ you aremigrating to the cloud and want to start on asolid foundation,
➡️ you want toreorganize your codebase,
➡️ you want tosimplify/standardize your technology stack,
➡️ you want tocoach your developers onbest practices for code andsecurity.

Specialization
Architecture, Platform Engineering, Cloud, Data, Microservices, Gitflow, CICD, code review, and developer coaching.

Tools/technologies/platforms:
GCP AWS Gitlab Github Terraform Ansible Python SQL Docker Kubernetes Bigquery Snowflake
  • French

    Native or bilingual

  • English

    Native or bilingual

Can work on-site
Paris (up to 50km), Marseille (up to 50km), Clermont-Ferrand (up to 50km), Nantes (up to 50km), Lyon (up to 50km)

Experience

  • Renault
    Lead Cloud DevOps & MLOps
    AUTOMOBILE
    January 2022 - Today (4 years and 7 months)
    Boulogne-Billancourt, France
    As 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.
    DevOps Google Cloud Platform (GCP) Cloud Architecture Agentic AI LLM
  • Autobiz (Groupe Stellantis)
    Data & AI Platform Architect (GCP)
    AUTOMOBILE
    April 2022 - December 2024 (2 years and 9 months)
    Courbevoie, France
    As 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.
    Google cloud CI/CD Terraform GCP AI Agents
  • SERVIER MONDE
    Lead Data Engineer
    PHARMACEUTICALS INDUSTRY
    October 2020 - March 2022 (1 year and 6 months)
    Paris, France
    2 projects:
    ETL pipeline creation tool (Python, Apache Beam & Dataflow) for medical data.
    Design, build & deploy of a data analysis environment

    PROJECT 1
    Design, 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 Terraform

    PROJECT 2
    On 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
    Google cloud Docker Python Argo CD Kubernetes

Reviews

5.0

Out of 2 ratings

B

Bruno

Autobiz

Reviewed on 5/12/2022

Thanks to his expertise, Wajdi was able to guide us towards architecture solutions that were very well suited to our needs. Excellent mastery of data-related topics (technologies, security, governance, etc.) as well as very good communication.
C

Camille

TWICE.AI

Reviewed on 10/6/2022

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Education

  • Polytechnic Engineer
    Ecole Polytechnique de Tunisie
    2014

Skill set

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