eRetail Engineering Manager

eRetail Engineering Manager / AI-Driven Delivery (all genders)

La description complète du poste couvre toutes les compétences associées, l'expérience antérieure et les qualifications que les candidats sont censés avoir.

Why Valtech?We’retheexperienceinnovation company-atrusted partnerto the world’s most recognized brands. To our people we offergrowth opportunities,avalues-driven culture,internationalcareersand the chance to shape the future of experience.

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

• The work we do and the innovation we drive
• Our values of share, careand dare
• A workplace culture that fosters creativity, diversity and autonomy
• Our borderless, global framework,which enablesseamless collaboration

The context

Valtech is a strategic partner for this client, responsible for the design, delivery, and operation of large-scale digital platforms across eRetail and Retail.

Having industrialized e-commerce delivery at scale, the engineering organization now needs a leader who can both run the factory — owning engineering and track the Delivery on quality, production performance day to day — and drive AI as a core acceleration lever across the engineering value chain: developer productivity, code quality, testing, and production operations.

This is not primarily a governance or transformation-program role. It is an engineering leadership role with direct delivery accountability, where AI adoption is a strategic priority embedded in how the factory operates, not a parallel initiative.

The role

Reporting to the Valtech Client Partner and Valtech Directors for this client, you own and lead engineering delivery within the client eRetail factory — build quality, delivery predictability, and production reliability — while driving the adoption of AI-native tooling and practices to accelerate engineering throughput and quality.

Act as the direct engineering leader for the factory, with hierarchical and operational accountability for the engineering teams (France/India), and as the AI adoption lead within engineering, in coordination with the AI Transformation Program Manager on cross-domain initiatives.

Key Responsibilities

Engineering & Delivery Ownership

• Own end-to-end engineering delivery for the eRetail factory: Technical roadmap, code quality standards, and release predictability.
• Manage and grow a distributed engineering organization across France; Ukraine and India, including hiring, mentoring, and career development.
• Ensure delivery cadence, quality, and reliability meet Louis Vuitton's business and seasonal (peak) requirements.
• Own the relationship between engineering and the Agile Operating Model, Quality & Testing, and Production & Support pilla rs from an engineering standpoint.

AI-Driven Engineering Acceleration

• Define and drive the AI adoption roadmap specifically within engineering: AI-assisted development, code review, refactoring, and technical debt reduction.
• Promote AI-native architectures and MLOps practices where relevant to eRetail platforms.
• Move AI-assisted engineering practices from pilot to standard practice across all squads — measured by adoption and productivity impact, not by number of POCs.
• Partner with the AI Transformation Program Manager to align engineering-level AI initiatives with the broader cross-pillar AI transformation roadmap.

Operational Excellence & Production Reliability

• Drive continuous improvement in engineering practices: CI/CD maturity, test automation, technical debt management, incident reduction.
• Own engineering-side KPIs: cycle time, code quality, defect rate, deployment frequency, and engineering cost efficiency.
• Ensure smooth build-to-run transitions with clear ownership handoff to Production & Support.

Governance & Stakeholder Management

• Represent engineering delivery and AI-in-engineering progress in relevant SteerCos and delivery reviews.
• Provide clear, structured reporting on engineering KPIs, AI adoption progress, risks, and dependencies.
• Escalate delivery or technical risks early with concrete, execution-ready mitigation plans.

Team Leadership

• Directly manage engineering leads across the factory; build technical career paths and succession within the team.
• Foster an engineering culture where AI tooling adoption is a shared practice, not an isolated initiative.
• Ensure consistency of engineering standar