AI Software Development Lifecycle Lead Engineer - T Cloud Public (REF5733O)

Location: Budapest, Szeged, Pécs, Debrecen, hu

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 
Lead AI-assisted software engineering activities for Meridian by designing repeatable SDLC patterns that help analyse, validate, document, and evolve complex cloud software stacks. The role anchors the engineering approach for OpenStack-derived services, repository-scale understanding, and sovereign software handover readiness. 

Role focus 
This senior position focuses on turning AI development platforms into disciplined engineering capability. The candidate should guide how coding agents, open-source or open-weight coding models, and enterprise-approved toolchains are used to accelerate code understanding, refactoring support, documentation, and transition readiness without weakening evidence quality or confidentiality. 

Key responsibilities 

• Define and lead AI-assisted SDLC patterns for repository intake, code exploration, service mapping, build diagnosis, documentation, and engineering evidence generation. 

• Guide analysis of OpenStack-derived control-plane services, APIs, dependencies, integration flows, and build structures across multiple repositories and teams. 

• Evaluate and operationalize AI development platforms, coding agents, and approved open-weight or Chinese coding model stacks for secure enterprise use cases. 

• Establish human-in-the-loop controls, quality gates, prompt libraries, reusable review patterns, and evidence standards for AI-generated engineering outputs. 

• Coach software engineers and platform specialists on safe, effective use of AI tools while coordinating with architecture, security, DevOps, and testing teams. 

• Produce senior stakeholder-ready artefacts including transition risks, service decomposition views, codebase maturity observations, and recommended engineering actions. 

Examples of market tools, models, and SDLC platforms expected 

• AI development environments such as Cursor, Windsurf, Claude Code, Continue, Cline, or VS Code-based extensions connected to enterprise-approved model endpoints. 

• Open-source, open-weight, or Chinese coding-capable models such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or similar models operated through approved controls. 

• Agentic and SDLC workflow components such as LangGraph, OpenAI Agents SDK, AutoGen, LlamaIndex, RAG pipelines, evaluation loops, and structured tool-calling patterns. 

• Engineering environments including GitHub Enterprise, GitLab, Jenkins, ArgoCD, Helm, Docker, Kubernetes, private package registries, and terminal-native automation workflows. 

Qualifications

Candidate profile 

• 8+ years in software engineering, platform engineering, or technical architecture roles, with proven ownership of complex engineering workstreams. 

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

• Deep practical experience using AI coding agents and LLM-enabled SDLC workflows for large codebases, technical documentation, and engineering acceleration. 

• Good understanding of OpenStack-derived cloud software architectures, modular service decomposition, CI/CD, Kubernetes-based delivery, and platform operations. 

• Able to lead senior engineers in ambiguous environments, challenge AI outputs, and convert incomplete evidence into structured, actionable engineering decisions. 

• Comfortable working in high-accountability, confidentiality-sensitive enterprise programs where auditability, traceability, and sovereignty constraints are mandatory. 

Additional Information

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.