Java software engineer engineering tools állás, munka

What awaits you? •Work as a fully integrated member of the financial reporting team, supporting daily operations. •Participate in system testing and optimization for AI-enabled financial tools. •Dive into diverse challenges: from AI chatbots, machine learning and data analytics to software...

• You will take a key role in developing our secure edge platform for real-time data processing applications.
• You will design, implement, and evolve robust, and observable platform components, APIs and SDKs for developing, deploying, and operating real-time applications.

Design, implement, and build data and AI solutions adding business value (Service Efficiency, Sales) – linking strongly to IOT data and other proprietary data sources...

• Data Product Development: Design, develop, and deploy scalable data products that provide meaningful insights to business stakeholders.
• Data Mart Infrastructure: Build and maintain a robust data mart infrastructure within AWS Redshift to support reporting needs.

Stakeholder Collaboration, Business Understanding & KPI Generation: Partner with business stakeholders to understand their needs, implement business logic and co-create impactful KPIs...

• Maintain and manage FI data operations, ensuring accuracy and consistency across systems
• Support annual planning templates and collaborate with business units using SAP BW and MS Power BI tools for planning cycles

• You develop and operate scalable, secure, and high-performance AI platforms in modern cloud environments.
• Additionally, you support the entire AI lifecycle - from data preparation through development and training to the productive operation of machine learning and generative AI solutions.

Developing innovative solutions that advance AI/ML systems for mobility services Conducting applied research in Agentic AI, including agent design, orchestration strategies, tool integration, and communication protocols Conducting research on AI safety and alignment topics Identifying research gaps...

• Collaborate with cross-functional teams to define data requirements and ensure data quality
• Support the data engineering team in reconciling data between the new and the legacy systems
• Participate in monitoring, troubleshooting, and resolving data processing issues