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 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.
- 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.
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 specialist services (medical, legal, wellness).
- 100% salary coverage during medical leave.
And many more advantages of being part of T-Systems!
If you are looking for a new challenge, do not hesitate to send us your CV! Please send CV in English. Join our team!
T-Systems Iberia will only process the CVs of candidates who meet the requirements specified for each offer.
