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AI Engineer; Operations & AI Transformation

Job in 1000, Brussels, Bruxelles-Capitale, Belgium
Listing for: Redion
Full Time position
Listed on 2026-07-01
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Job Description & How to Apply Below
Position: AI Engineer (Operations & AI Transformation)
Redion (Europ Assistance), was founded in 1963 and is a pioneer of the assistance concept. In our operations center, we advise and support Austrian customers 24 hours a day – 365 days a year – and rely on a global network of 750,000 partner companies.
Our core areas include Travel, Mobility, Home & Connected Living, Cyber Security, Health & Senior Care. We provide our customers with tailored solutions both in difficult situations and in everyday life.
Our successful company is currently undergoing a major transformation process, both in terms of system landscape and by leveraging synergies within the group.
In Northern Europe, at Unit level (Belgium, Germany, Switzerland and Austria) we are  accelerating an ambitious AI-driven transformation  to reshape how assistance is delivered across:
Mobility (roadside assistance), travel assistance, travel claims, customer service, fraud & leakage, sales, and support functions
Our objective:  industrialize AI at scale  to improve:
Operational efficiency, customer experience, decision-making, and automation and productivity. All within a strong framework of  governance, compliance, and responsible AI .

As an AI Engineer, you will have a Transformation role and will design, build, deploy, and operate AI solutions that support real operational use cases across the 4 countries of the Unit and the different business lines as Mobility, Travel assistance, Travel claims, Customer Service, Claims, Fraud, Back-Office, Sales, and Support functions.
You will work closely with Operations, IT, Data, and Digital teams, while strictly adhering to AI governance frameworks (GDPR, EU AI Act, Generali Group standards).
You will be in touch with the stakeholders of the Unit to gather the business needs and opportunities for AI implementation, listing, analyzing and structuring the needs and initiatives considering their impact, feasibility, complexity and cost to propose efficient prioritization.
You will have a clear focus on Business impact considering AI having to impact positively on productivity, cost, CX, ROI.

Key Responsibilities
AI Use Case Design & Delivery (Solution Design & AI Product mindset)
Design and develop AI/ML solutions for fraud detection, claims automation, document analysis, conversational AI (voicebots, chatbots, Whats App), and decision support
Build end-to-end AI pipelines from prototype to production (data → model → integration → monitoring)
Build Agent copilots & decision support tools
Implement AI on concrete use case to increase efficiency as in Operations (dispatching, call automation, claims triage, etc…)
Ownership of outcomes (automation, AHT, better CX, reduction of customers interactions with platform, etc…)
LLM & NLP Engineering
Integrate Large Language Models into business workflows
Implement RAG architectures, prompt engineering, and evaluations
Enable knowledge assistants, Case summarization, automation of repetitive tasks, etc…
AI Ops / MLOps
Deploy and operate scalable AI solutions in production
Implement monitoring, versioning, and performance tracking
Business & Transformation Impact
Collaborate with stakeholders to Identify high-value use cases, Assess feasibility, complexity, and ROI, and Prioritize initiatives at Unit level
Drive measurable outcomes, such as Automation rate increase, Reduction in Average Handling Time (AHT), Cost per case reduction, Customer satisfaction improvement
Governance, Risk & Compliance
Ensure compliance with GDPR, EU AI Act, and Generali standards
Contribute to AI documentation such as model cards and risk assessments
Cross-Functional Collaboration
Act as a bridge between business and technology and   Support business teams with feasibility analysis and AI risk reviews
Promote AI best practices across Northern Europe Unit

Bachelor's or Master's degree in Computer Science, AI, Data Science, or similar.
3+ years of hands-on experience in AI / ML engineering.
Python skills and experience with ML frameworks.

Experience with NLP, LLMs (RAG, prompt engineering), APIs, and cloud deployment (Azure preferred).
Understanding of data governance, GDPR, and responsible AI principles.
Good communication skills and Innovation oriented.
Fluent in…
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