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• Design and build artificial intelligence and machine learning solutions for enterprise clients
• Operationalize AI and machine learning solutions combining custom models with cloud and third-party AI services
• Assess client needs and data for AI/ML solutions

• Design and code clean, maintainable and high-performance custom-build solutions based on Java technologies and related frameworks
• Follow defined methodology and standards to create software of high quality
• Conduct code reviews and provide constructive feedback to team members

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• Active involvement in the software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms including software models, development boards and shipping products

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• 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

• Operating a mobile communication platform for corporate IOT devices
• Analysing API related issues
• Providing 3rd level application support
• Executing SQL fixes through CI/CD pipelines
• Problem management of assigned tickets
• Organizing virtual meetings with other departments and SW vendors

• Deployment, configuration and management of Atlassian products (JIRA Service Management, Confluence, Jira)
• Design and implementation of CI/CD pipelines for automated deployments and integrations
• Maintenance and improvement of system reliability, scalability and security

• Build and maintain scalable, reliable, and secure environment on AWS using Infrastructure as Code tools
• Oversee the deployment, configuration and management of clusters
• CI/CD pipeline development with designing and managing CI/CD pipelines, Infrastructure as Code, and GitOps toolset and skillset

• Responsibility for Identity & Access Management (IAM)
• Deployment, management, and customization of Keycloak in an Amazon EKS environment using modern CI/CD tools
• Support and optimization of the Microsoft Active Directory infrastructure

• 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

• 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 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

• 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

• Assistance in setting up and maintaining CI/CD pipelines
• Monitoring application and infrastructure performance
• Identification of application errors and configuration issues
• Collaboration with team members to streamline workflows and optimize system performance

• Build and maintain production-grade AI infrastructure using Infrastructure as Code
• Optimise performance and cost efficiency of LLM workloads
• Develop and maintain CI/CD pipelines tailored for AI workloads
• Support agent-tool integration patterns using MCP and production infrastructure

• 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