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• Tackling complex technical challenges focused on scalability, reliability, and speed
• Maintaining a high-performance infrastructure that processes millions of events with low latency
• Collaborating with Data Scientists and Engineers to design and implement cutting-edge feature topologies

• Development of a robust framework for generating and distributing work across all operations
• Creation of tools and frameworks for designing specific workflows
• Establishment of a comprehensive reference for a 360-degree view of customer data

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients
• Development of highly scalable services realizing AI/ML functionalities

• Producing high quality code for the full technological stack from database to UI
• Assisting with troubleshooting basic issues and improving application performance
• Documenting and demonstrating solutions with a focus on security and performance

• Design, build, deploy, maintain, and continuously improve Microsoft Copilot Studio agents
• Establish and manage governance standards for Copilot Studio and Power Platform environments, ensuring security, compliance, and effective lifecycle management

Review business requirements and ensure alignment with end-to-end customer journeys, translating needs into user stories, technical specifications and architecture designs....

• Do you want to lead SoftwareOne’s indirect channel business in Hungary? 
• Are you motivated to recruit, develop, and grow a high-performing partner ecosystem? 

• Design and build agentic systems that plan, call tools and automate real business workflows
• Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Design and enforcement of data architecture standards including Delta Lake / Lakehouse architecture and data modeling

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékeivel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Manual and automated testing across iOS and Android platforms
• Collaboration with developers, designers, product owners, and fellow QA engineers
• Definition and refinement of test strategies for new functionality and release cycles

• Lead the design and development of Power BI reporting and analytics solutions for enterprise clients,
• Facilitate workshops and meetings with business stakeholders to understand reporting and analytical requirements,
• Translate business needs into functional and technical specifications,

• 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
• Maintaining coding standards, version control practices, and agile routines

EZEK LESZNEK A FELADATAID • MES fejlesztő kolléga munkájának támogatása • MES funkciók fejlesztésében való segítségnyújtás • Gyártósori adatok elemzésében való részvétel ...

• Setup and maintenance of IT cloud infrastructure for multiple products
• Setup and maintenance of the automated build/deployment jobs
• Maintenance of various support tools and utilities
• Monitoring application performance and resource planning

• Creation of demo concepts and AI-centric tools based on guidance, customer needs, and platform capabilities
• Support of development and implementation of demos showcasing product value
• Setup and troubleshooting of demo hardware and partner integrations

• Real-time risk assessments using machine learning
• Ownership of risk infrastructure for Instant ACH in the US market
• Collaboration with software engineers, data analysts, and data scientists to design rules and refine ML models
• Support for chargeback and fraud investigation teams

• Writing production-quality, well-tested scraper code in Python
• Learning the architecture of the collection platform including scrapers, proxy layer, queues and enrichment API
• Debugging issues across multiple components using logging, monitoring and alerting tools

• High-performance simulation loops, autonomous behavior, and data-oriented design
• Improve system performance, proactively indetify technical debt
• Understanding and optimize complex dataflows
• Designing, improving, extending existing architecture
• Create technical specification based on business needs

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks