A
Procurement - AI lead
ArcelorMittal
lu
1d ago
92%
Strong
Job description
Key Responsibilities Business & Requirements Analysis Actively participate to business process optimization workshops Collaborate with business stakeholders to identify challenges and opportunities where AI can add value. Translate business goals into technical requirements for AI solutions. Identify use cases where AI adds real value, prioritizing ROI and feasibility. Solution Design Design end-to-end AI solutions, covering: Data ingestion and processing Model training and evaluation Deployment, monitoring, and scaling Ensure the design is scalable, maintainable, and secure. Model & Technology Selection Evaluate and recommend GenAI models, frameworks, and AI services. Decide between custom development and external tools Collaboration & Cross-Functional Leadership Work closely with: Data Scientists — to ensure models meet business objectives Software Engineers / Developers — for integration into applications AI Technical architects Act as a bridge between business, internal and external consulting teams and our implementation partners Governance, Compliance & Risk Ensure AI solutions follow ethical guidelines, avoid bias, and comply with regulations (GDPR, HIPAA, AI Act, etc.). Ensure all AI solutions adhere to internal governance policies and procedures. Prototyping & Proof-of-Concepts Build or oversee prototypes / PoCs to validate technical feasibility and business impact. Assess performance, accuracy, and latency of AI models in the target environment. Documentation & Communication Produce architecture diagrams, solution specifications, and technical documentation. Present AI solution designs and clearly explain technical trade-offs to stakeholders and leadership. What We’re Looking For Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Information Technology, or a related field. 4+ years of hands-on experience in AI Solutions in procurement domain. A very broad experience in different types of AI solutions: different technology stacks, different tooling, in-house and SaaS applications, … Ability to evaluate what works and what doesn’t, what is mature and what isn’t. Proven experience deploying AI solutions in Microsoft Azure and SAP technologies Familiarity with LLMs and generative AI frameworks Knowledge of model monitoring, retraining, and explainability techniques. Excellent communication, collaboration, and stakeholder management skills. English: Advanced (written and spoken). Knowledge about Finance business processes Knowledge about Purchasing business processes is a plus