E learning állások V. kerületben (programozó, fejlesztő)

• Design and implement core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer
• Build and maintain entitlement decision cache with invalidation on entitlement changes

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• Real-time decision making with machine learning for risk assessments
• Ownership of risk infrastructure for Instant ACH in the US market
• Cross-functional collaboration with software engineers, data analysts, and data scientists

• Joining junior team assisting with latest projects
• Learning skillset necessary to contribute including working with source code and applying development processes
• Attending online brainstorming sessions regularly
• Learning best practices and key technologies to quickly become productive

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Maintaining and evolving data structures
• Building new ETL flows and maintaining/improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

• Writing and maintaining clean, high-quality, and efficient code that aligns with project specifications using AI tools daily to accelerate delivery
• Executing comprehensive testing and seamless deployment of programs and systems

• Development of infrastructure providing insights into operational cost and risk associated with Wise product ownership
• Enhancement of product to reduce Wise's cost for customers and enable smoother experience when additional information is required

• Build, operate, and improve production data pipelines using Python, Airflow, Kubernetes, and related technologies
• Design scalable data pipelines and data models for growing data volumes and processing needs

• Learning existing system architecture, codebase, tools, and development practices
• Validating existing technical documentation and flagging any gaps or outdated content
• Highlighting blockers to knowledge transfer such as missing info, unclear logic, inaccessible systems

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML and MLOps projects
• Ensuring successful execution of cloud migration projects

• Partner with engineering teams to identify the highest-leverage AI opportunities in the developer workflow
• Own foundational architecture and standards for how agents model releases and internal tools are evaluated and deployed internally

• Backend and frontend development with focus on high-performance and speed
• Cooperation with product team including UX, UI, and product management
• Building and coding backend in Node.JS and frontend in React in a complex web application
• Participation in and conducting code reviews

• Learning and understanding software feature functionality on a detailed logical level
• Developing a project plan including project scope, release schedule, milestones, deliverables
• Communicating project status
• Articulating a vision and direction to the development team

• Development and customization of Microsoft Dynamics 365 applications using C#/.NET and Power Platform tools
• Building integrations between Dynamics 365 and Azure services such as Logic Apps and Functions

• Design and implement core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer
• Build and maintain entitlement decision cache with invalidation on entitlement changes

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Design and implement algorithms to process and analyze sensor data from sources like LiDAR, images, and satellite imagery
• Create algorithms to transform sensor data into actionable insights, such as reconstructing 3D models, segmenting spatial data, or detecting environmental features

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...