Senior Data & AI Architect / Technical Lead (Cloud & GenAI)

• +5 years in software development, architecture, or AI/ML solutions.
• Experience developing with LLMs and GenAI (OpenAI, Azure OpenAI, Bedrock, Vertex AI).
• Knowledge of RAG, agents, prompt engineering, and model evaluation.
• Experience with cloud architectures (AWS, Azure, or GCP) and microservices.
• Proficiency in Python (Node.js or Go is a plus).
• Experience with API Gateways (Kong, NGINX, Apigee) and system integrations.
• Knowledge of CI/CD and Infrastructure as Code (Terraform, CloudFormation).
• Experience in security (IAM, authentication, authorization).
• Multi-LLM architectures and vendor decoupling.
• MCP and Agent-to-Agent (A2A) architectures.
• LLMOps / MLOps and model observability.
• Security, guardrails, and responsible AI use.

• Experience leading teams or technical initiatives.
• Cloud certifications.
• Experience in regulated environments.
• Knowledge of agent frameworks (LangChain, Semantic Kernel).

• English B2 or higher.

What is it like to work at Deloitte?

🤩 High-impact projects where you will have a long career and learning path

☯️ Hybrid-flexible day-to-day: you will have flexible hours and a good balance between remote work and teamwork in our offices or those of our clients

⚽ Good atmosphere inside and outside the office: you will enjoy several team-building activities per year, cultural and sports activities... and much more!

🧘♀️ Comprehensive well-being: take care of yourself with our physical, mental, and financial health program... and with a medical team in the offices!

🤲 Social impact: You can sign up for a large number of national and international volunteering opportunities and pro-bono projects to put your time and talent at the service of those who need it most

🗣️Feedback and continuous learning culture: you will grow in an inclusive environment where equal opportunities and your personalized training plan will boost your development. Can you already see yourself at the Deloitte University in Paris?

🤝 Exclusive benefits for being part of Deloitte: you will be able to enjoy a wide catalog of benefits and a comprehensive flexible compensation plan

The GenAI Expert role is responsible for leading the design, development, and industrialization of generative AI capabilities within the organization. This profile combines a solid technical foundation with strategic vision and execution capability, acting as the bridge between business, architecture, and engineering to ensure efficient, secure, and scalable adoption of GenAI.

You will be the technical reference for generative models (LLMs and multimodal models), defining reference architectures, integration standards, and best practices for their use in corporate environments. You will actively participate in designing advanced solutions such as virtual assistants, autonomous agents, and RAG-based systems, ensuring alignment with business needs.

You will also lead the evolution of GenAI integration platforms (GenAI Gateway), enabling controlled model consumption through security patterns, observability, and governance. You will play a key role in technology assessment, validation through proof of concept, and production deployment.

The GenAI Expert will also promote responsible AI adoption, establishing control, evaluation, and regulatory compliance mechanisms. As a technical leader, you will collaborate with multidisciplinary teams, promote standards, accelerate GenAI adoption, and contribute to value generation through innovation.

• Design and develop LLM-based applications (agents, assistants, RAG systems).
• Build APIs, microservices, and inference pipelines integrated with corporate systems.
• Apply techniques such as prompt engineering, response evaluation, and output optimization.
• Define scalable and secure architectures for GenAI solutions.
• Design and evolve GenAI Gateway-type platforms for model consumption management.
• Establish patterns for MCP and A2A architectures, ensuring interoperability between agents and services.
• Integrate models from providers such as OpenAI, Azure OpenAI, AWS Bedrock, or Vertex AI.
• Implement gateways and integration solutions (Kong, NGINX, Apigee, etc.).
• Ensure integration with IAM, networks, observability, and CI/CD.
• Define quality, cost, and performance metrics for generative models.
• Implement security, privacy, and responsible AI controls.
• Establish governance frameworks for model consumption and monitoring.
• Lead the deployment of solutions in production environments.
• Automate infrastructure using IaC and DevSecOps practices.
• Develop reusable components and accelerate adoption.
• Act as a technical reference and mentor for multidisciplinary teams.
• Define the technical roadmap and promote best practices.
• Evaluate new technologies and identify innovation opportunities.

• Strategic thinking with an execution-oriented mindset.
• Strong communication skills with both business and technical stakeholders.
• Technical leadership and collaboration in complex environments.