Enterprise Architect (Specialized in AI)
Objective:
The Enterprise Architect specialized in AI is responsible for defining, designing, and implementing the Technological enterprise-wide artificial intelligence strategy in collaboration with Data Science Competence Center and Data Analytics & AI Competence Center. They lead the adoption of scalable and secure AI architectural frameworks, integrating them into existing IT systems and Enterprise Architecture to minimize costs and maximize service and performance, aligned with corporate objectives.
Responsibilities:
- Define and design the enterprise AI architecture framework to support AI solutions
- Support stakeholders to formulate code approaches to solve problems using algorithms and data sources in context of customer, engineering, and business needs.
- Guide AI platform selection (cloud, on-prem, hybrid) and integration with existing enterprise systems and architecture
- Participate in Enterprise Architecture reviews and provide technical oversight with his/her AI competences
- Collaborate with other stakeholders of AI environment, in evaluating new AI technologies, vendors, and tools for enterprise adoption.
- Participate together with the DevOps team in choosing the best operational architecture.
- Monitor the performance of the framework & platform components of the AI Solutions. In the event of poor performance, support the development team (Data Science Competence Center and Data Analytics & AI Competence Center ) in implementing the best technological solution within the operational architecture.
- Have a strong relationship with Infrastructure team and the development team so that he/she can support their activity when building scalable, secure, performing solutions within technological platform and architecture strategy.
Qualifications:
- 5 to 10 years of engineering experience using large data systems on SQL, Hadoop, Spark, etc.
- 5 to 10 years of experience using one or more programming or scripting language like Python, Scala, PySpark or C# to work with data.
- 5 to 10 years of experience using tools like Python, R, MATLAB, AMPL, SAS, and other relevant data science tools/environments. (Jupyter Notebook)
- 5 to 10 years of experience developing AI and ML pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD automation; and DevOps principles
2 to 4 years of prior experience implementing HTTP REST APIs.
2 to 4 years of experience working in Azure Cloud designing scalable AI Solutions and integrated them with other systems.
2 years of experience implementing GenAI solutions.
2 years of releasing and maintaining GenAI solutions in productive environments.
1 year of starting, projecting and testing Agentic AI solutions and frameworks.
- Have strong knowledge about data engineering concepts, tools and automation processes (DataOps) since data pipelines and architectures provide the base for building AI solutions as all-in-one Databricks
5 to 10 years of experience of the insurance business and its business processes in all its areas (transversal vision)
Skills and Competencies:
- Strong stakeholder written and verbal communication and documentation skills
- Objective Oriented
- Accountable; takes ownership and pride in their work
- Flexibility and adaptation to changing environments.
- Ability to work in an agile scrum project team
- Customer Orientation.
- Complex problem-solving and analytical skills
- Strong written and verbal communication skills
- Be able to explain the AI Framework to software developers
- Continuous improvement and creativity.
- Passion to learn world class techniques and tools.
- Ability to multi-task, prioritize and be detail-oriented
Other requirements:
- More than 8 years of work experience
- Prior leadership pr architecture board experience.
- Degree in Computer Science, Statistics, Mathematics, Economics, or similar.
Master in Artificial Intelligence will be preferred.
- Fluent written and spoken English. (Level C1)
- Italian and Spanish knowledge will be valuable.
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