Louis Vuitton Data & AI Tech Manager

Louis Vuitton is a premier luxury house within the LVMH group, renowned for its craftsmanship, creative excellence and global retail presence. As an employer, Louis Vuitton blends heritage brand standards with investment in digital innovation, offering cross-disciplinary teams the opportunity to deliver cutting-edge solutions for luxury retail and operations.

1. Maintain and curate an inventory of data assets (databases, sources, formats) to ensure accessibility, organization and governance.
2. Design and implement robust data extraction and integration pipelines to ingest information from internal and external sources and enable seamless data flow across systems.
3. Manage and optimize databases and storage solutions to support efficient retrieval, processing and long-term data retention.
4. Partner with business units to translate requirements into analytics, reporting and AI-enabled applications; oversee selection and deployment of BI tools and data visualization platforms.
5. Architect and deliver agentic AI systems, including scalable multi-agent orchestration frameworks and advanced Retrieval-Augmented Generation (RAG) pipelines that integrate Knowledge Graphs, hybrid search and re-ranking models.
6. Design memory and state management solutions (short- and long-term) using vector DBs, SQL or key-value stores to preserve context across interactions.
7. Own the end-to-end SDLC for AI applications: prototype, productionize, and operationalize agents with latency, cost and reliability constraints in mind.
8. Develop human-in-the-loop interfaces, evaluation and automated testing frameworks to measure task completion, hallucination rates and tool invocation reliability.
9. Implement guardrails, deterministic workflow enforcement, observability stacks and cost/token governance to ensure safe, auditable and economical agent operation.
10. Provide technical leadership: evaluate agent frameworks, define stack standards, drive POC-to-production criteria and mentor engineering teams in prompt engineering and non-deterministic system design.

1. Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Data Science or a closely related technical discipline (or equivalent industry experience).
2. Proven track record designing and delivering production AI/ML systems, particularly LLM-based applications, RAG solutions and multi-agent architectures.
3. Demonstrated experience with data engineering, database optimization and building scalable data pipelines in cross-functional environments.
4. Prior experience leading technical teams or projects, with the ability to mentor engineers and align technical roadmaps with business objectives.
5. Strong stakeholder management and product collaboration skills, able to convert ambiguous business needs into actionable technical specifications.

1. Retrieval-Augmented Generation (RAG)
2. Multi-agent orchestration
3. vector DBs
4. SQL
5. key-value stores
6. Knowledge Graphs
7. hybrid search
8. re-ranking models
9. LLMs
10. BI tools
11. data visualization software
12. prompt compression
13. model routing
14. asynchronous processing
15. observability stacks
16. workflow engines
17. Human-in-the-Loop (HITL) interfaces

Senior-level experience delivering production-grade AI and data systems, typically 5+ years in data engineering or ML/AI engineering roles with at least several years in technical leadership or project ownership.

Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Data Science or equivalent professional experience.

Louis Vuitton combines the rigor of a heritage luxury Maison with a forward-looking digital agenda, promoting meticulous attention to detail and high standards across functions. Teams operate in a collaborative, cross-disciplinary environment where technical innovation is applied to enhance client experience and operational excellence.