IT Manager overseeing the design and delivery of enterprise infrastructure services across cloud and data centers. Leading a team to ensure scalable platforms for project execution and business continuity.
About the role
- Enterprise Architect specialized in AI for Reale ITES defining and implementing technological AI strategies. Collaborating across teams to enhance AI integration and performance metrics.
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 in implementing the best technological solution within the operational architecture.
- Have a strong relationship with Infrastructure team and the development team to support their activity in building scalable, secure, performing solutions
Requirements
- 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.
- Strong knowledge about data engineering concepts, tools and automation processes (DataOps).
- 5 to 10 years of experience of the insurance business and its business processes in all its areas (transversal vision)
Benefits
- 12gg di smartworking al mese
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