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Deutsche Telekom

Deutsche Telekom is a leading global telecommunications company and the largest network provider in Europe by revenue. Headquartered in Bonn, Germany, the firm offers fixed-line broadband, mobile network services, internet solutions, and enterprise IT services worldwide. It is best known internationally for its mobile operations under the T-Mobile brand and its corporate IT services division, T-Systems.

As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries.

DT-ITS recieved the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.

    Mission

    Support Meridian technical due diligence and transition readiness by using AI-assisted software engineering methods to understand OpenStack-derived cloud services, reconstruct service boundaries, diagnose dependencies, and accelerate the creation of high-quality handover documentation.

    Role focus

    This position targets service-level analysis of modular cloud software, especially control-plane components, API surfaces, integration dependencies, configuration models, and runtime assumptions. The candidate should use AI development platforms pragmatically to speed up engineering work while maintaining strong human review and traceable evidence.

    Key responsibilities

    • Analyse OpenStack-style services and surrounding components to map APIs, configuration flows, service dependencies, database usage, and operational assumptions.

    • Use AI coding agents to accelerate code navigation, call-flow reconstruction, interface analysis, and technical documentation across large multi-repository environments.

    • Support build and test diagnosis for selected services, including dependency resolution, container build issues, runtime configuration gaps, and reproducibility problems.

    • Create structured service handover artefacts such as service maps, dependency notes, API summaries, risk observations, and onboarding documents for receiving teams.

    • Work with DevOps, testing, security, and architecture specialists to validate AI-assisted findings and turn them into actionable engineering backlog items.

    • Identify technical debt, maintainability risks, hidden coupling, missing documentation, and areas where automated analysis should be complemented by expert review.

    Examples of market tools, models, and SDLC platforms expected

    • AI coding environments such as Cursor, Windsurf, Claude Code, Cline, Continue, or VS Code-based AI extensions for large-repository engineering workflows.

    • Coding-capable models such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or other approved open-weight and enterprise model stacks.

    • OpenStack-related components and patterns such as Nova, Neutron, Cinder, Keystone, Glance, Horizon, Heat, placement services, message buses, and Kubernetes integrations.

    • Supporting engineering tools such as Git, GitLab, Jenkins, Docker, Kubernetes, Helm, ArgoCD, Python tooling, API clients, log analysis tools, and dependency scanners.

    Candidate profile

    • 5+ years in software engineering, cloud platform engineering, DevOps-oriented development, or technical software handover roles.

    • Strong Python skills plus experience in at least one backend or systems language such as Go, Java, C, C++, or Rust.

    • Practical experience using AI-assisted development tools for codebase exploration, documentation generation, refactoring support, or build issue triage.

    • Good understanding of OpenStack-derived architectures, cloud control planes, distributed services, APIs, CI/CD, container delivery, and Linux-based environments.

    • Strong analytical discipline for separating AI suggestions from evidence-backed findings and producing concise technical outputs for engineering stakeholders.

    • Comfortable working in confidential enterprise environments with high expectations on traceability, quality of documentation, and structured handover readiness.

    Please note: remote working is only possible from within Hungary due to European taxation regulations.

    * Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.

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    Work setup

    Location
    Budapest
    Remote work
    Remote (Hungary)
    Employment
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