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• Design, build, and maintain robust CI/CD pipelines
• Manage and optimize cloud infrastructure on T Cloud Public, ensuring high availability and performance
• Administer and troubleshoot Linux and Windows systems in production environments

• Building AI-assisted development workflows for code understanding, documentation, build triage, and handover preparation
• Implementing workflow utilities, prompt packs, repository analysis scripts, documentation helpers, and integration adapters

• 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

• Kialakítás és üzemeltetés ügyfelek részére dedikált sandbox környezetek
• Infrastruktúra automatizálás Terraform vagy Bicep használatával
• Fejlesztés GitLab alapú deployment pipeline-ok

• 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

• Design, build, and operate enterprise-grade Agentic AI platforms
• Own architecture and delivery
• Mentor engineers
• Partner closely with client and internal teams
• Run secure AI environments at scale under strict regulatory and security requirements
• Architect Zero-Trust environments for LLM-based solutions

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

• Operation and evolution of Kubernetes platform
• Building, configuring, and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Design and operation of NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Develop native Swift/iOS applications
• Design user interfaces and functions as planned
• Participation in requirements gathering, project and technical planning
• Writing Unit and UI tests and participation in developer testing
• Continuous learning

• Design, implement, and maintain backend services using Java 25 and Spring Boot 4.1
• Evolve the existing modular monolith toward a cleaner hexagonal architecture
• Implement and secure OAuth 2.0/OIDC identity and access management flows and APIs
• Develop and maintain RESTful APIs and service interfaces

• Design and build secure infrastructure foundation for AI-assisted software development
• Operate Kubernetes environments hosting AI engineering tools and services
• Implement GitOps and Infrastructure as Code patterns for provisioning and configuration

• Design landing zones, network topology (hub-spoke, transit gateway), and identity/federation models across AWS, Azure, and/or GCP
• Define infrastructure-as-code patterns (Terraform, Bicep/ARM, CloudFormation, or Pulumi) that other teams build on
• Design for HA/DR, resilience, and multi-region setups

• 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

• Gherkin mondatok implementálása és testreszabása Java nyelven Selenium keretrendszerrel
• Tesztelők támogatása SOAP- és REST-alapú webszolgáltatások tesztelésében megfelelő teszteszközök használatával
• Tesztkeretrendszerek és -eszközök implementálása és fejlesztése JUnit, Mockito, Selenium használatával

• Strengthen Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

Establishment and operation of the build, release, and observability backbone for Meridian technical due diligence, code quarantine, reproducible software validation, controlled deployment preparation, and reliable engineering handover across cloud platform components...

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

• Service-level analysis of modular cloud software
• Mapping APIs, configuration flows, service dependencies, database usage, and operational assumptions of OpenStack-style services and surrounding components

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