AI Engineering Workflow Developer (mf/d), hibrido

documenting repeatable SDLC usage patterns. Create scripts and lightweight services that connect Git repositories, CI/CD logs, issue trackers, documentation stores, and internal model endpoints. Help prepare handover materials including codebase summaries, service notes, build observations, glossary entries, and structured evidence templates. Test open-source, open-weight, and Chinese coding models in approved environments and document strengths, limitations, risks, and practical usage guidance. 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 AI development environments such as Cursor, Windsurf, Continue, Cline, Aider, Claude Code, or VS Code-based extensions configured for enterprise repositories. Model families used for coding support such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or other internally

approved models. Workflow and integration tooling such as Python, FastAPI, notebooks, LangChain, LlamaIndex, GitLab/GitHub APIs, Jenkins APIs, Markdown, and documentation automation. Supporting engineering tools such as Git, Docker, Kubernetes basics, Helm basics, Linux shells, package managers, log processing, and structured prompt repositories. Qualifications 2-4 years in software engineering, DevOps automation, data engineering, AI tooling, or platform-adjacent development roles. Good Python skills and willingness to work across APIs, scripting, developer tooling, documentation, tests, and lightweight automation services. Hands-on familiarity with AI coding assistants, prompt engineering, LLM APIs, local model experimentation, or RAG-style development is strongly preferred. Basic understanding of Git, CI/CD, Linux, containers, cloud platforms, and software architecture documentation, with readiness to deepen OpenStack knowledge. Careful working style with good documentation habits, curiosity, and ability to escalate unclear findings instead of over-trusting AI-generated answers. Comfortable working in a confidential enterprise environment where learning speed, quality discipline, and structured communication are important. Additional Information What do we offer you? Work environment flexibility International, dynamic and collaborative environment. T-Social: social initiatives (sports, community, health, …). Hybrid work model (remote/on-site). Flexible working hours. Growth development Customized training: access to Coursera to learn whatever you want, whenever you want. Weekly language classes (English German). International Mentoring Sessions Experience Days. Compensation benefits Flexible compensation plan (health insurance, meal vouchers, childcare, transport). Telemedicine. Life and accident insurance. Social fund. Wellbeing time off 26+ working days of vacation per year. Free access to speci

AI Engineering Workflow Developer (mf/d) AI Engineering Workflow Developer (mf/d) Granada, Spain Employees work in a hybrid mode Full-time Company Description T-Systems is part of the Deutsche Telekom Group, with around 30.000 employees worldwide. We create technology with purpose to generate a positive impact on society. We are looking for curious talent, eager to learn, take on challenges, and contribute ideas that transform our customers experience. We trust people: we offer autonomy, continuous support, and a collaborative environment where you can grow without limits. We are one global team, guided by respect, integrity, and a passion for doing better every day. Job Description Key responsibilities Implement and maintain small AI-assisted engineering utilities for repository indexing, code summarization, dependency extraction, log parsing, and documentation generation. Support senior engineers in configuring AI development environments, testing prompts, comparing model outputs, and