Python állások, munkák középiskolai végzettséggel

• On-premise IT infrastruktúra üzemeltetése
• On-premise IT infrastruktúra támogatása
• On-premise IT infrastruktúra folyamatos fejlesztése
• Linux alapú rendszerek adminisztrációja
• Kubernetes klaszterek adminisztrációja
• Middleware komponensek adminisztrációja
• Automatizációs feladatok megvalósítása

• Keeping airline applications up and running
• Ensuring high availability and stable operations
• Monitoring systems and handling alerts
• Opening, managing and coordinating incidents
• Executing planned maintenance tasks
• Keeping contact with providers and internal technical teams

• Kapcsolattartás az ügyfelekkel, igények felmérése és tanácsadás
• Azure Function App fejlesztés
• Dokumentálás
• Programozás Pythonban
• Azure infrastruktúra tervezés és karbantartás
• Rendszeres ellenőrzés, frissítés és teljesítmény optimalizálás Azure környezetben
• Fejlesztések tervezésében aktív részvétel

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

• Management of end-to-end software release process including branch management
• Software version control
• Release note documentation
• Communication with internal and external collaborators
• Enhancement of CI/CD pipelines for release automation
• Defect logging and tracking for releases

• Building reusable AI-assisted workflows for repository intake, code scanning, dependency extraction, build issue triage, and documentation generation
• Packaging prompts, retrieval steps, tool integrations, and evaluation logic into repeatable engineering patterns suitable for enterprise delivery

• 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 (Full-stack, AI, Data)

• Clarification and adaptation of requirements into the software environment under development
• Installation, configuration and administration of software solutions
• Creation and maintenance of technical documentation

• Architecture of cloud-native AI applications integrating LLMs, vector search, and real-time data
• Design of end-to-end web solutions from frontend to backend
• Implementation of RAG pipelines, model serving, and AI agents in production
• Leadership of cross-functional teams (Full-stack, AI, Data)

• Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components

• 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

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• Building end-to-end web solutions from UI to backend
• Leading and contributing to development efforts across the full stack
• Design and implementation of web applications using modern frameworks and best practices
• Translating business and user needs into intuitive, scalable technical solutions

• CI/CD pipeline-ok kialakítása, fejlesztése és karbantartása
• Deployment és release folyamatok automatizálása
• Cloud infrastruktúrák üzemeltetése és optimalizálása
• Konténerizált környezetek kezelése (Docker, Kubernetes/OpenShift)
• Monitoring, logging és alerting rendszerek kialakítása és üzemeltetése

• Work with an agile mindset and according to agile methodology
• Collaboration within the team, with other teams in the Domain and Deutsche Telekom, and with software engineers using the cloud platform
• Approach work with a DevOps and continuous improvement mindset

• Building, configuring and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Designing and operating NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• Delivery of complex data engineering projects
• Leading small delivery teams
• Management of customer relationships
• Supporting pre-sales processes
• Mentoring junior engineers
• Contributing to hiring data talent

• Development and Implementation of Infrastructure-as-Code (IaC) Solutions (e.g., Terraform, Ansible).
• Automation of Recurring Tasks such as deployments, scaling, and troubleshooting.
• Building and Maintaining CI/CD Pipelines for fast and secure software delivery.

• Pioneer technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Gain new insights by bringing together rich semantic context with large scale business data.