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AI and Data Engineering lead


Overview

In this role, you will lead the AI & Data Engineering agenda to accelerate Vanderlande’s AI-native transformation of the engineering value stream. You will shape strategy, translate priorities into a focused program, and drive end-to-end AI-enabled engineering transformations across multiple domains. You’ll build reusable AI capabilities, data products, and reference patterns while ensuring governance and responsible AI. This is a high-impact leadership position with cross-functional collaboration and a clear focus on reducing lead times and increasing quality and time-to-market.

Arbeidsvoorwaarden / Benefits
  • 40 vacation days
  • Flexible working hours
  • Hybrid workplace (40% home / 60% office)
  • Health & Wellbeing budget
  • Commuting allowance with public transport reimbursement
  • Working from home allowance (remote support)`,`Collective pension scheme and health insurance discount`,`On-site health centres with gym and therapists`,`Vanderlande Academy and training facilities`,`Lease car/compensation option`,`Short-term incentive earnings potential
Verantwoordelijkheden
  • Define and execute the Technology AI and data strategy and portfolio for Vanderlande’s Technology unit
  • Translate technology priorities into a prioritized AI/data initiative roadmap
  • Align AI/data roadmap with product domain strategies and ETO-toCTO transformation
  • Own the AI/data portfolio, roadmap, and prioritization process
  • Identify opportunities to reduce engineering lead times, rework, and improve quality
  • Ensure investments deliver measurable improvements in throughput and time to market
  • Redesign engineering workflows to embed AI-enabled capabilities across disciplines
  • Reduce handoffs and fragmented data by creating unified engineering information flows
  • Develop and scale the Engineering Configurator and other AI solutions
  • Create AI-enabled data products and knowledge structures for reusability
  • Integrate AI with BOM, CAD, PLM, ALM and software development platforms
  • Establish multidisciplinary fusion teams and communities of practice
  • Partner with external institutions and customers to accelerate capability development
  • Build AI knowledge across engineering populations and introduce AI tooling alongside standards and training
  • Ensure AI solutions comply with governance, security, and IP protections
  • Measure adoption by outcomes, not just tool usage
  • Establish evaluation methods for AI-generated engineering outputs
  • Move solutions from experimentation to operational use with ICT, Data, Security, Legal, Quality and AEC
  • Launch AI-enabled initiatives with measurable impact on cycle-time, throughput, and quality
  • Develop performance dashboards tracking time to market, throughput, adoption, reuse and quality
Belangrijkste vereisten
  • 12+ years in engineering/technology development
  • 7+ years leading AI initiatives
  • Proven track record transforming complex engineering or product-development environments
  • Experience applying AI, data and automation to improve throughput, quality or time to market
  • Strong understanding of generative AI, ML, intelligent agents, RAG and AI-enabled software engineering
  • Experience with data architecture and data products
  • Familiarity with BOM, CAD, PLM, ALM, simulation, software development and test automation
  • Experience building multidisciplinary teams and product-based delivery models
  • Ability to translate technical opportunities into measurable outcomes
  • Experience in industrial automation, logistics, or software-intensive engineering environments
  • Proven ability to develop capabilities and lead organizational change
  • Strong collaboration with engineers, architects, product leaders and executives
  • Knowledge of governance, security, data sovereignty, and responsible AI practices
  • entrepreneurial and execution-oriented mindset
  • strategic vision
  • stakeholder management
  • AI, data and automation in engineering
  • knowledge of generative AI, ML, autonomous agents, RAG
  • data architecture and data products

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