Role Description
Support technical due diligence and transition readiness by using AI-assisted software engineering methods to understand complex codebases, reconstruct dependencies, diagnose builds, accelerate documentation, and improve handover readiness in enterprise cloud and platform environments. A core objective of the role is to help analyse and evolve a cloud software stack derived from OpenStack, including its service decomposition, control-plane components, interfaces, and build structure.
This position targets repository-scale code understanding, dependency discovery, build and compile diagnosis, technical documentation generation, and AI-assisted support for software handover activities in an enterprise setting. The candidate should be comfortable working with a modular cloud platform architecture based on OpenStack-style services and surrounding infrastructure components.
Key Responsibilities
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Analyse large software repositories to map services, dependencies, interfaces, build flows, and technical risks relevant to technical due diligence.
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Reconstruct the architecture of a cloud software stack derived from OpenStack, including key service boundaries, integration points, APIs, and operational dependencies.
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Use AI coding agents and structured prompting patterns to accelerate code understanding, reverse engineering, and documentation generation across large codebases.
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Support build-log diagnosis, compile issue triage, and reproducibility analysis across CI/CD pipelines and container-based delivery environments.
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Produce structured handover artefacts including architecture summaries, dependency maps, code quality observations, and readiness assessments for receiving engineering teams.
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Work closely with software architecture, DevOps, testing, and security specialists to convert AI-assisted insights into actionable engineering outputs.
Examples of Market Tools and Models Expected
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AI coding environments such as Windsurf, Cursor, Claude Code, or VS Code-based AI extensions for large-repository engineering workflows.
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Frontier coding models such as Anthropic Claude Opus-class models and newer, high-capability coding models used through enterprise-approved interfaces or bring-your-own-key setups.
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Supporting engineering tools such as GitHub Enterprise, GitLab, Jenkins, ArgoCD, Helm, Docker, Kubernetes, and terminal-native automation workflows.
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Familiarity with OpenStack-oriented cloud software environments and adjacent components such as Nova, Neutron, Cinder, Keystone, Glance, and Kubernetes integration patterns is highly valuable.
Qualifications
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5+ years in software engineering, platform engineering, or DevOps-oriented development roles, with recent hands-on work on LLM-enabled engineering workflows preferred.
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Strong coding skills in Python plus experience in at least one systems or backend language such as Java, Go, C, C++, or Rust.
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Solid understanding of Git, CI/CD, container builds, Kubernetes-based delivery, and software architecture analysis.
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Experience with codebase exploration, reverse engineering, technical debt identification, and engineering documentation in complex environments.
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Good working knowledge of cloud platform architectures derived from OpenStack, including modular service design and multi-component integration patterns, is strongly preferred.
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Comfortable working in high-accountability enterprise settings with strong expectations on confidentiality, evidence quality, and structured deliverables.
Additional Information
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You will be working in the European Union to meet our customers' data security and privacy requirements.
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Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.
