ironquill.tech/board

$ cat jobs/ai-swe-agentic-sdlc-workflow-engineer-t-cloud-public-ref5735-deutschetelekomitsolutions-0f0339a39767.json

AI SWE / Agentic SDLC Workflow Engineer - T Cloud Public (REF5735F)

Deutschetelekomitsolutions·Worldwide·Budapest, Szeged, Pécs, Debrecen, HU·mid
pythonci/cdgit
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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 Industrialize AI-assisted engineering workflows for Meridian by packaging repeatable patterns that support codebase intake, dependency extraction, build triage, documentation generation, and technical evidence creation across cloud software work packages. Role focus This position emphasizes reusable workflow engineering. The candidate should combine Python, APIs, orchestration frameworks, retrieval patterns, and AI development platforms to create governed workflows that can be reused across repositories, OpenStack-derived services, CI/CD outputs, architecture documentation, and handover evidence. Key responsibilities Build reusable AI-assisted workflows for repository analysis, code scanning, service decomposition, dependency discovery, build diagnosis, and documentation generation. Package prompts, tools, retrieval layers, model routing, evaluation checks, retries, and human approval steps into repeatable engineering accelerators. Integrate AI workflows with Git platforms, CI/CD systems, documentation stores, issue trackers, test outputs, service catalogues, and architecture evidence repositories. Create workflow outputs that remain auditable, including traceable source references, confidence indicators, reviewer checkpoints, and explicit assumptions. Experiment with open-source, open-weight, and Chine

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