AI Engineering Workflow Developer
Posted 10 Sep 2026
Advertised as “AI Engineering Workflow Developer - T Cloud Public (REF5739F)”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 2–4 yrs
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
No salary listed for this role.
Company Description
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.
Job Description
Mission
Support Meridian engineering teams by building, testing, and maintaining AI-assisted development workflows that accelerate code understanding, documentation, build triage, and handover preparation for cloud software and platform work packages.
Role focus
This position supports senior AI SWE and platform specialists by implementing workflow utilities, prompt packs, repository analysis scripts, documentation helpers, and integration adapters. The candidate should be eager to learn enterprise cloud platforms, AI development tooling, and disciplined software handover practices.
Key responsibilities
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Implement and maintain small AI-assisted engineering utilities for repository indexing, code summarization, dependency extraction, log parsing, and documentation generation.
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Support senior engineers in configuring AI development environments, testing prompts, comparing model outputs, and documenting repeatable SDLC usage patterns.
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Create scripts and lightweight services that connect Git repositories, CI/CD logs, issue trackers, documentation stores, and internal model endpoints.
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Help prepare handover materials including codebase summaries, service notes, build observations, glossary entries, and structured evidence templates.
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Test open-source, open-weight, and Chinese coding models in approved environments and document strengths, limitations, risks, and practical usage guidance.
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Participate in reviews with senior engineers to validate AI-generated outputs, correct inaccuracies, and improve workflow quality over time.
Examples of market tools, models, and SDLC platforms expected
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AI development environments such as Cursor, Windsurf, Continue, Cline, Aider, Claude Code, or VS Code-based extensions configured for enterprise repositories.