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Connecting Europe's Fixed Income MarketsOne connected fixed income ecosystemRead moreSeamless listing, trading, clearing and settlement for fixed income
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Connecting Europe's Fixed Income MarketsOne connected fixed income ecosystemRead moreSeamless listing, trading, clearing and settlement for fixed income
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Connecting Europe's Fixed Income MarketsOne connected fixed income ecosystemRead moreSeamless listing, trading, clearing and settlement for fixed income
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CSD
European CSD modelBuilding the CSD of Choice in EuropeRead moreEuronext Securities is shaping the future of European capital markets by enhancing integration, connectivity, and innovation.
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Technology
Euronext Technology SolutionsHigh-Frequency Trading Solution (HFTS)Read moreThe new generation of high-frequency risk trading platforms, offering the highest performance with ultra-low latency and minimal jitter, all at a low total cost of ownership.
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Data
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Indices
Access the white paperNext generation of indicesRead moreThis white paper marks the second edition of Euronext’s Index Outlook series, a recurring publication designed to give investors deeper insight into our index innovation agenda and the structural forces shaping global markets.
- Regulation
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About Euronext
Euronext strategic planInnovate for Growth 2027Read moreShaping capital markets for future generations
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- R28532 - AI Integration Engineer
AI Integration Engineer
Team Mission
We are creating and new AI R&D Team in Dublin that will operate as a dedicated innovation capability within IT Corporate Functions, reporting to the Head of Software Development, and working in close collaboration with the IT-CF AI team based in Porto.
The team's mission is to research, design, prototype, and validate AI-driven solutions that enhance business processes and automation across the Euronext Group. The team will focus on emerging AI technologies, intelligent automation, machine learning, generative AI, and integration patterns that delivery teams across the organisation can adopt and industrialise.
The Dublin-based team will:
- Explore and validate new AI technologies and approaches.
- Design future-state AI architecture and integration patterns.
- Develop PoCs and minimum viable products (MVPs).
- Contribute to Euronext's AI strategy and technology roadmap.
- Deliver reusable AI capabilities and accelerators.
- Partner with business stakeholders to identify and assess new AI opportunities.
- Collaborate closely with the Porto AI team to transition successful R&D initiatives into scalable enterprise solutions.
Role Purpose
The AI Integration Engineer is responsible for integrating AI capabilities into business applications and enterprise platforms while ensuring quality, reliability, and maintainability.
The role combines software engineering, integration engineering, and quality assurance responsibilities to ensure AI solutions can be successfully adopted within the Euronext technology landscape.
Key Responsibilities
- Design and develop integration components that connect AI services to enterprise applications.
- Build APIs, middleware components, and automation services supporting AI solutions.
- Integrate AI capabilities with platforms such as Dynamics 365, Microsoft 365, Power Platform, and other Corporate Functions systems.
- Define and implement reusable integration patterns for future AI initiatives.
- Design, develop, and maintain automated quality assurance frameworks for AI solutions.
- Create functional, integration, regression, and performance test suites.
- Validate AI outputs, workflows, and business process integrations.
- Collaborate with the Porto AI team to ensure consistency of architecture and technical standards.
- Support deployment automation and operational readiness activities.
Required Skills
- Strong software engineering background.
- Experience with .NET, C#, Python, REST APIs, and cloud-native architectures.
- Experience integrating enterprise applications and SaaS platforms.
- Knowledge of Azure Integration Services and Power Platform.
- Experience developing automated testing frameworks.
- Understanding of quality assurance methodologies for AI-enabled solutions.
- Strong troubleshooting and analytical skills.
Success Measures
- Successful integration of AI solutions into business platforms.
- Automated test coverage of AI-enabled applications.
- Reduction of production defects and integration issues.
- Delivery of reusable integration and testing frameworks for future AI initiatives.