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• Design and maintain automated pipelines for legacy .NET deployments and modern containerized/Kubernetes workflows
• Automate provisioning and management of infrastructure using Terraform, Ansible, or Bicep

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

• 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

• 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

• Definition and driving of cloud products and platforms evolution
• Collaboration with engineering teams and stakeholders across Deutsche Telekom
• Definition of product vision, strategy, and roadmap for cloud products and platforms
• Understanding of customer needs, market trends, and business priorities

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

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources

• Architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines
• Building scalable, production-grade LLM services and agentic workflows alongside traditional ML systems

• Development and implementation of complex generative AI applications from discovery to deployment
• Establishment of best practices framework for deploying cloud architectures supporting AI agents
• Creation of RAG/LLM evaluation pipelines, embedding strategies, and optimization of prompts/runtime

• AI infrastruktúra építése és karbantartása Infrastructure as Code (Terraform/CDK) használatával
• AI ügynökök gyors és biztonságos telepítésének támogatása monitoringgal, naplózással és telepítési automatizálással

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• End-to-end SRE ownership for the Global Fabric service
• Incident ownership across the customer journey from detection to resolution
• Primary operational escalation point for CF-related incidents
• Escalation of complex technical issues and coordination of resolution activities

• End-to-end felelősség cloud és on-premise platformok architektúrájáért
• Cloud platformok tervezése és fejlesztése (AWS, Azure, T Cloud Public)
• Kubernetes-alapú üzemeltetési és deployment megoldások kialakítása
• Shared és managed service architektúrák megtervezése és továbbfejlesztése

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

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

• Design and implement cloud security controls across AWS, Azure, and GCP
• Build security automation using CI/CD pipelines, Infrastructure as Code, and Policy as Code
• Develop automated compliance checks and remediation workflows

• 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, develop, and maintain automated test suites as code using Java
• Create BDD-based automated test scenarios using Cucumber against REST APIs
• Automate API testing for OAuth 2.0 and OpenID Connect (OIDC) authentication and authorization flows using RestAssured or similar tools

• Business process analysis and design of Lead-to-Order processes
• Cross-country process harmonisation
• Requirements engineering
• Business workshops and stakeholder alignment
• Fit-gap and impact analysis
• End-to-end solution definition
• Backlog readiness and delivery support
• Business validation