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• Design, deploy, and manage cloud infrastructure on Microsoft Azure
• Implement and maintain Infrastructure as Code (IaC) using Terraform
• Automate configuration management and application deployments using Ansible
• Build, optimize, and support CI/CD pipelines for continuous integration and delivery

Architecture & Infrastructure: Set standards for infrastructure, access, and deployment with IT, security, and the ML & AI engineers. Build all AI platform components with Terraform on top of the AWS foundation and GitLab setup of our cloud engineering team....

• Your responsibility: From day one, you'll own your stories and take end-to-end responsibility for your tasks.
• Your team: You'll work in a small team of no more than five full-stack engineers. Like this, our teams are more efficient and can move fast.

• 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

• 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

• Design, develop and maintain document templates in an OMS / CCM environment
• Create layouts aligned with corporate design (CI/CD) standards
• Clarify document requirements with business stakeholders and translate them into solutions

Participate in our Product Sprints: collaborate on planning, requirements and design. Develop the Livingdocs platform across frontend, backend, databases, search and APIs, making smart use of AI-assisted tools....

• 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

• Take ownership of the operational delivery of the Azure Foundation within a broader cloud transformation program.
• Translate existing technical requirements and architecture designs into structured work packages, project plans, milestones and deliverables.

• 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

• Fejlesztés és megvalósítás komplex generatív AI alkalmazásokban a felfedezéstől a bevezetésig
• Legjobb gyakorlatok keretrendszerének kialakítása felhőarchitektúrák telepítéséhez AI ügynökök támogatására, költség, teljesítmény és biztonság fókuszával LLM munkaterhelésekhez és vektor kereséshez

Design and maintain comprehensive solution architecture and technical design documentation, while delivering robust integration and backend solutions for enterprise applications and services...

• 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

• Building and maintaining production-grade AI infrastructure using Infrastructure as Code, monitoring, logging, and deployment automation
• Optimising performance and cost efficiency of LLM workloads through autoscaling, caching, batching, and infrastructure right-sizing

• Ownership of architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines including retrieval strategy, chunking, indexing, and monitoring

• 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