Descripción de la oferta
ppAs the AI Engineering Platform Lead, you serve as the central technical authority for the enterprise AI capability. Reporting to the IT Department and functionally to the Head of Digital Transformation, this foundational IT leadership role is responsible for the industrialization of AI across the organization. /p pYour objective is to establish the infrastructure, governance, and technical talent required to scale AI initiatives. While the Digital Transformation office identifies business opportunities, defines the global strategy and manages project delivery, you own the technical execution—ensuring every solution is built on a robust enterprise platform, adheres to established engineering standards, and is managed with operational efficiency. /p ul liIT Architecture Core: You ensure the AI ecosystem is a core component of the IT landscape, integrated with enterprise network, security, and data platform architectures. /li liLine vs. Functional Leadership: You provide Line Management for the Data Scientists and AI/ML Engineers overseeing their career progression, upskilling, and technical output quality. /li liFunctional Alignment: While technical staff report functionally to Project Managers for daily execution, you maintain authority over the technical frameworks and standards they utilize. /li /ul h3Responsibilities /h3 pbEnterprise AI Infrastructure Architecture /b /p ul liPlatform Strategy: Own the strategic roadmap and oversee the technical health of the enterprise AI platform, primarily utilizing Azure Machine Learning or Azure Databricks. /li liSystems Integration: Ensure the AI ecosystem is integrated with the broader IT environment, specifically regarding Network architecture, Security protocols, and Enterprise Data platforms. /li liArchitectural Design: Develop reference architectures and infrastructure patterns (covering LLMs, Computer Vision, and Predictive Analytics) to provide reusable components for AI teams. /li /ul pbTechnical Governance Standards /b /p ul liEngineering Frameworks: Establish and enforce company-wide technical standards across the AI lifecycle, including coding practices, model versioning, and testing protocols. /li liCompliance Risk: Collaborate with the Security to integrate data privacy, ethical AI guardrails, and model auditing into the automated development pipelines. /li liTechnical Validation: Act as the final authority on AI deployment patterns to ensure system maintainability, security, and long-term architectural alignment. /li /ul pbTalent Stewardship Capability Building /b /p ul liLine Leadership: Act as the dedicated line manager for the community of Data Scientists, and AI/ML Engineers. /li liProfessional Growth: Own the career tracks, upskilling programs, and technical certifications, ensuring the talents remain at the forefront of AI advancements. /li liResource Allocation: Orchestrate the assignment of technical talent into cross-functional project squads, providing the necessary technical oversight to maintain quality during delivery and technically leading some initiatives. /li /ul pbOperational Excellence Innovation /b /p ul liService Reliability: Lead the post-production support and maintenance of deployed AI products, ensuring high availability and performance against enterprise SLAs. /li liFinOps Observability: Optimize the AI compute footprint through cost-attribution models and advanced monitoring for model drift and system health. /li liTechnology Assessment: Monitor the AI ecosystem to evaluate emerging technologies and engage with research communities or vendors (e.g., Microsoft) to maintain institutional knowledge. /li /ul pbArchitecture Platform Strategy /b /p ul liAzure Management: Significant experience in the strategic oversight of Azure ML and Databricks within a large-scale, regulated corporate environment. /li liIT Infrastructure: Technical knowledge of the intersection between AI and IT infrastructure, specifically Networking, Security, and Data Platforms. /li liDesign Proficiency: Demonstrated ability to create reference architectures for diverse AI workloads (LLMs, RAG, Predictive Analytics). /li liTechnical Validation: Experience serving as a technical gatekeeper or "Design Authority," reviewing solution architectures for maintainability, security, and scalability. /li /ul pbEngineering Lifecycle Expertise /b /p ul liSDLC for AI: Comprehensive knowledge of the end-to-end AI lifecycle, including data ingestion, automated CI/CD, and production monitoring. /li liSoftware Discipline: Proficiency in software engineering best practices (unit testing, modularity, version control) as applied to AI/ML. /li liMLOps/LLMOps Standards: Experience defining and enforcing enterprise-grade operational standards for model deployment, validation, and performance tracking /li liLifecycle Support Maintenance: Proven experience managing the post-production support, maintenance, and reliability of mission-critical AI systems. /li /ul pbLeadership Matrix Navigation /b /p ul liPersonnel Management: Proven experience in the line management of technical staff, with a focus on career development and upskilling. /li liStakeholder Synthesis: Ability to navigate matrix organizations and collaborate with Architecture, Security, and Digital Transformation leaders. /li /ul pbFoundations /b /p ul liExperience: 8+ years in IT or Engineering; 5+ years in a leadership role focused on AI platform. /li liEducation: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field. /li liLanguages: Professional fluency in English; proficiency in French is strongly preferred. /li liOrganizational Awareness: Clear understanding of the distinction between AI Platform management, Data Platform management, and Data Engineering/BI functions. /li /ul pWhat we offer /p ul liA competitive compensation package /li liA yearly education budget to steep your learning curve /li liA yearly sport budget because a fit body leads to a fit mind /li liA flexible working culture because your work-life balance matters to us /li liA position that enables you to have an impact on 1’000s of people, and the whole company's growth. /li liAn international, knowledgeable, and passionate team with a strong collaborative mindset /li /ul pCheck our LinkedIn and website to learn more about us don’t hesitate to contact us if you have any questions. /p /p #J-18808-Ljbffr
