Platform Architect

We are seeking a highly experienced AI Platform Architect to join our team in France and lead the design, implementation, and evolution of enterprise-scale AI, Machine Learning, and Generative AI platforms. The ideal candidate will be responsible for defining scalable, secure, resilient, and cloud-native AI architectures that enable data-driven innovation, AI adoption, and digital transformation initiatives. The AI Platform Architect will collaborate with business stakeholders, data scientists, AI engineers, platform teams, cloud specialists, security teams, and third-party vendors to establish AI technology roadmaps, architecture standards, and best practices for AI platform engineering.

Key Responsibilities
· Define and own the enterprise AI platform architecture strategy and roadmap aligned with business objectives.
· Design and implement scalable AI/ML and Generative AI platforms across cloud, hybrid, and on-premises environments.
· Lead architecture initiatives supporting AI transformation, MLOps, LLMOps, automation, and platform engineering.
· Collaborate with business and technical stakeholders to translate AI use cases into scalable technical solutions.
· Establish and enforce AI architecture standards, governance frameworks, and best practices.
· Design and implement AI solution architectures including LLMs, RAG frameworks, Vector Databases, Knowledge Management platforms, and Intelligent Automation solutions.
· Drive integration strategies across AI platforms, data platforms, APIs, cloud services, and enterprise applications.
· Ensure AI solutions meet security, compliance, scalability, performance, and reliability requirements.
· Lead architecture reviews and provide technical leadership throughout AI project lifecycles.
· Define and promote MLOps, LLMOps, CI/CD, Infrastructure-as-Code (IaC), observability, monitoring, and AI platform automation standards.
· Evaluate emerging AI technologies and recommend innovative solutions aligned with business goals.
· Partner with security, governance, and risk teams to ensure Responsible AI and regulatory compliance.
· Mentor engineering and data teams while promoting AI engineering excellence and innovation. Required Skills & Qualifications
· Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Information Technology, or a related field.
· 10+ years of IT experience, including at least 5 years in AI Architecture, Data Architecture, Platform Architecture, or Cloud Architecture roles.
· Proven experience designing and implementing enterprise-scale AI and data platforms.
· Strong expertise in cloud technologies, preferably Microsoft Azure, AWS, or Google Cloud Platform.
· Hands-on experience with Azure AI Services, Azure OpenAI, Databricks, AWS AI/ML, Vertex AI, or similar AI platforms.
· Strong understanding of Machine Learning, Generative AI, Large Language Models (LLMs), NLP, RAG architectures, Vector Databases, and AI application frameworks.
· Experience with containerization and orchestration technologies such as Docker, Kubernetes, or OpenShift.
· Strong knowledge of microservices architecture, API management, event-driven architectures, and distributed systems.
· Experience with DevOps, MLOps, LLMOps, CI/CD pipelines, Infrastructure-as-Code, and automation frameworks.
· Proficiency with Terraform, Ansible, Azure DevOps, GitHub, GitLab, Jenkins, or similar technologies.
· Strong understanding of data governance, AI governance, platform security, identity management, and compliance requirements.
· Experience with monitoring, observability, model performance monitoring, and AI operational platforms.
· Excellent communication, leadership, and stakeholder management skills.
· Ability to engage with both technical teams and senior business stakeholders. Preferred Qualifications
· Experience within Banking, Financial Services, Insurance, or other regulated industries.
· Cloud certifications such as Azure Solutions Architect Expert, Azure AI Engineer Associate, AWS Solutions Architect Professional, or Google Professional Cloud Architect.
· TOGAF, SAFe, or equivalent architecture certifications.
· Experience with Platform Engineering, Internal Developer Platforms (IDP), and AI Platform Engineering.
· Hands-on experience designing and deploying GenAI solutions including Copilots, Chatbots, Virtual Assistants, and Knowledge Management platforms.
· Knowledge of Responsible AI, AI Risk Management, Model Governance, and AI Security frameworks.
· Familiarity with Zero Trust Security, FinOps, and Site Reliability Engineering (SRE) principles.
· Experience working in Agile and product-centric delivery environments.