Python fejlesztő állások, munkák I. kerületben

• Administration and support of enterprise DNS, DHCP and IPAM services using CygnaLabs QIP
• Management of DNS zones and DNS records (A, AAAA, CNAME, PTR, MX, TXT, SRV)
• Configuration and maintenance of DHCP scopes, reservations, exclusions, options and lease management

• Development of advanced technical solutions for infrastructure and services expansion and operation
• Preparation of procedures for the complete life cycle of cloud-native based production environment of packet Core including 5G-SA

• Writing clean, maintainable Python code and automation scripts (bash/shell)
• Building CI/CD pipelines and deployment automation for AI systems
• Creating infrastructure as code and configuration management solutions (terraform)
• Developing APIs, microservices, and event-driven architectures

• Perform web, network, and infrastructure penetration tests independently.
• Actively participate in red team exercises (e.g., initial access, lateral movement, persistence).
• Document test results and deliver detailed, client-friendly reports.

• Technology architect with T Cloud Public hands-on experience
• Deep expertise in public cloud architecture
• Strong understanding of VPC networking
• Strong understanding of IAM & federation
• Strong understanding of cloud security architecture
• Strong understanding of Kubernetes & container platforms

• Tesztmenedzsment feladatok vezetése a teljes tesztfolyamat szakmai kísérésével az igényfelméréstől a riportolásig
• Követelményanalízis fejlesztőkkel, üzemeltetőkkel és más érintettekkel közösen
• Tesztstratégiák tervezése, tesztelési lépések meghatározása és követése

• Design and maintain automated CI/CD pipelines
• Automate provisioning and management of infrastructure using Infrastructure as Code tools
• Manage health and performance of mission-critical applications
• Implement advanced monitoring, logging, and tracing for legacy and modern services

• Identifying, developing, and implementing AI-driven solutions
• Supporting colleagues in creating AI-powered solutions including agents, workflow automations, and analytics tools
• Monitoring developments in AI, Generative AI, and digital productivity tools

• Analysis of global service quality data including non-conformance costs, corrective and preventive actions, customer satisfaction, NPS, and audit findings
• Transformation of analysis into clear conclusions and prioritized recommendations for regions, central functions, and management

• Measuring performance of multi-channel patient recruitment campaigns
• Optimizing multi-channel patient recruitment campaigns
• Forecasting performance of multi-channel patient recruitment campaigns
• Translating recruitment data into actionable insights
• Accelerating enrollment
• Reducing site burden

• Improvement of repetitive processes using AI
• Organization and checking of data used by the Operations team
• Connecting everyday tools to reduce manual work
• Experimentation with AI tools, chatbots and workflows
• Troubleshooting and solving smaller operational tasks

• 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

Shaping and evolving the architecture of MDO network automation capabilities including reusable automation patterns, interfaces and technical guidelines...

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

• Technikai menedzsment és fejlesztés a csapat felhőalapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint
• Üzleti logika adatmegoldássá történő átalakítása multinacionális csapatban

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, dataset documentation

• 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)

• Experience in different data science topics including machine learning, LLM, deep learning
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements

• Automatizált UI és end-to-end tesztek fejlesztése webalkalmazásokhoz
• Automatizált UI és end-to-end tesztek karbantartása webalkalmazásokhoz
• Automatizált UI és end-to-end tesztek stabilizálása webalkalmazásokhoz
• Webes tesztautomatizálási keretrendszerek használata és továbbfejlesztése

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines