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• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

• Design landing zones, network topology and identity/federation models across AWS, Azure, and/or GCP
• Define infrastructure-as-code patterns that other teams build on
• Design for HA/DR, resilience, and multi-region setups

• Technical leadership post-sales for strategic customers in big data projects
• Design and implementation of big data projects from architectural design to data engineering and model deployment

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

Work directly with clients, product owners, architects, and development teams to understand business and technical requirements and translate them into infrastructure and cloud architecture requirements...

• Development, maintenance, and support of cloud-based data operation infrastructure and production data pipelines
• Design, implementation, operation, and optimization of Azure data services and Databricks workloads

• Stable operation of highly available applications in a 24/7 environment
• Monitoring of applications
• Deployment of applications
• Continuous improvement of applications
• Contribution to operational excellence
• Support of the entire application lifecycle from deployment to productive operation

• Developing and maintaining backend components in Golang
• Working in an agile environment and contributing to development and end-to-end testing
• Taking ownership of code and maintaining high quality standards
• Code review and testing
• Collaborating with internal partners and airline customers

• Building AI-powered automation for complex cloud engineering environments
• Combining platform engineering, software development and cloud expertise with modern Generative AI technologies to automate parts of the software development lifecycle

• Biztonsági és kockázati értékelések végzése alkalmazások és rendszerek esetében
• Frontier AI szkennelési képesség beállítása, technikai eredmények elemzése és backlog kezelése
• Jira backlogok létrehozása, kezelése és megoldása biztonsági kérdések, kivételek és kockázati tételek esetén

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines including IaC scanning and policy-as-code

• Administration, configuration and maintenance of Microsoft Dynamics 365 Business Central and Dynamics 365 CRM platforms
• Collaboration with various departments to gather business requirements and deliver tailored Dynamics 365 solutions

• Architect cloud-native AI applications integrating LLMs, vector search, and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines, model serving, and AI agents in production
• Lead cross-functional teams including Full-stack, AI, and Data

• Planning, designing, implementing, and maintaining Rust components and applications
• Building a unified SDK for AI-based features integration into Aether
• Reviewing requirements and contributing to feature design
• Implementing clean, idiomatic, maintainable Rust code

• Design and implementation of a SUSE-based virtualization platform using KVM as the hypervisor
• Certification and optimization of the platform for SAP workloads including sizing, high availability, and performance requirements

• Design, develop, and maintain automated and manual test cases
• Application of different test classification approaches by access level, purpose, execution type
• Implementation of effective testing strategies based on Test Pyramid, Testing Honeycomb, Testing Trophy

• Nemzetközi csapat tagjaként hosszú távú tesztelési feladatok különböző projektekben
• Új automatizálási keretrendszer fejlesztése low-code tesztautomatizáláshoz
• A keretrendszer karbantartása, gondozása és folyamatos továbbfejlesztése
• Innováció és új technológiák aktív bevonása és alkalmazása

• Komplex AI megoldások fejlesztése ügyfelek számára
• RAG alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal
• Open source LLM-ek integrálása ügyfélrendszerekbe cloud és on-premise környezetben Kubernetes használatával

• Skálázható cloud-native adatarchitektúrák tervezése Databricks vagy MS Fabric platformokra
• Adatmodellek, sémák és tárolási minták kialakítása (lakehouse, Delta, Parquet)
• Batch és streaming adatok betöltési pipeline-jainak megtervezése
• ETL/ELT folyamatok és transzformációs stratégia meghatározása

• Coordination of operations together with Data Center, IaaS and PaaS layers
• Coordination and support of network lifecycle activities including installs, upgrades, changes, and firmware updates
• Management of network interconnections and related documentation