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Salary
≈ $79k – $185k per year (Estimated)
Location
In office (Genk)
Seniority
Architect · 7+ years exp

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Jul 28, 2026.

Overview
Company
Impact
Profile match
Aperam is a stainless steel company with 2.5 million tonnes of flat stainless and electrical steel production capacity across Brazil and Europe, serving 40+ countries through its Recycling and Renewables segment.

We are looking for aAI Solutions Architect

Location

Genk/Luxembourg

Mission

With 11,600 employees of 47 nationalities, 2.5 million tonnes of flat stainless and electrical steel capacity in Brazil and Europe, and an industrial network concentrated in six production facilities across Brazil, Belgium, and France, Aperam is a truly global industry leader. According to our values of agility and ingenuity, we collaborate with customers to design tailor-made, innovative, and long-lasting solutions to their most challenging needs.

To accelerate the AI transformation program, we are looking for an AI Solution Architect. As an AI Solutions Architect, you will drive Aperam's AI transformation. You will identify, design, and deliver high-impact AI solutions across the business, acting as the bridge between strategic ambition and technical execution in a complex, multi-site industrial environment.

This is a rare greenfield opportunity: you will define how AI is architected, governed and scaled at Aperam, working across the enterprise. Equally at home in the boardroom and in code, you will combine deep technical expertise with sharp business acumen to build a sustainable, enterprise-wide AI capability.

Accountabilities

Key Responsibilities

AI Strategy & Portfolio

  • Define and evolve Aperam's enterprise AI strategy, aligned with business priorities across Enterprise and Industrial domains.
  • Build and manage a prioritised AI use case portfolio, balancing short-term value delivery with long-term transformational initiatives.
  • Develop compelling business cases and ROI frameworks to support investment decisions and executive sponsorship.

Stakeholder Engagement & Change

  • Partner with senior business leaders across functions and geographies to identify pain points and translate them into AI opportunities.
  • Champion AI literacy and change management, supporting teams through the adoption of new AI-powered tools and ways of working.
  • Communicate complex AI concepts clearly and credibly to non-technical audiences, including executive and C-suite stakeholders.

Solution Architecture & Delivery

  • Architect end-to-end AI/ML solutions, from data ingestion and model development to deployment and monitoring, across cloud and on-premise environments.
  • Co-ordinate technical design and delivery, working closely with data engineers, data scientists and IT teams.
  • Define AI architecture standards, governance frameworks and data principles to ensure solutions are scalable, secure and maintainable.
  • Drive adoption of AI capabilities where they create genuine business value.

Vendor & Ecosystem Management

  • Evaluate, select and manage AI technology vendors and platforms in partnership with IT and Procurement.
  • Monitor the external AI landscape and bring relevant emerging capabilities into Aperam in a structured, value-focused way.

Capability Building

  • Recruit, build and develop a high-performing AI team including data scientists, ML engineers and AI specialists.
  • Establish communities of practice and knowledge-sharing mechanisms to scale AI capability across the organisation.

Profile

As a an AI Solution Architect, you:

  • 7+ years of experience in data, analytics or AI roles, with at least 3 years in a senior enterprise AI or solutions architecture capacity.
  • Proven track record of delivering end-to-end AI/ML solutions in complex, multi-stakeholder environments, ideally from scratch.
  • Experience in industrial, manufacturing or supply chain contexts is a strong advantage.
  • Background in building or scaling an AI function, including portfolio management and business case development.

Technical Skills

  • Strong hands-on proficiency with machine learning frameworks (e.g. scikit-learn, TensorFlow, PyTorch) and MLOps practices.
  • Deep experience with cloud platforms (Azure, AWS or GCP), data engineering pipelines and modern data architectures (data lake, lakehouse).
  • Nice to have proficiency in programming languages such as Python and SQL; experience with LLM integration, RAG pipelines and GenAI application development is highly desirable.
  • Solid understanding of data governance, model explainability and responsible AI principles.

Business & Leadership Skills

  • Strong ability to translate business problems into AI solutions, and AI outputs into measurable business value.
  • Excellent stakeholder management and communication skills, including demonstrated ability to influence at senior levels.
  • Experience developing AI roadmaps, managing delivery portfolios and presenting to executive leadership.
  • Entrepreneurial mindset; comfortable operating in ambiguous, fast-moving environments with a bias for action.
  • Languages: Fluency in English is required; proficiency in French or Dutch is an advantage.
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