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 auditable workflow outputs with traceable source references, confidence indicators, reviewer checkpoints, and explicit assumptions.
- Experiment with open-source, open-weight, and Chinese coding models to compare their usefulness for SDLC automation and handover tasks.
- Translate ambiguous engineering questions into structured AI-assisted workflows and validated deliverables for work-package leads.

Requirements

- 5+ years of engineering experience across software development, DevOps automation, platform engineering, or AI workflow implementation.
- Strong hands-on Python skills and API integration experience.
- Practical knowledge of orchestration frameworks, RAG patterns, tool calling, and evaluation loops.
- Experience turning prototypes into reusable engineering workflows with clear interfaces, logging, error handling, configuration,



and maintainability.
- Good understanding of CI/CD, Git workflows, containers, Kubernetes, software architecture documentation, and modular cloud software environments.
- Strong written communication skills for workflow documentation, evidence packs, usage guidance, and decision support for senior stakeholders.
- Ability to work in ambiguous, confidentiality-sensitive settings where AI outputs must be reviewed, justified, and converted into reliable engineering evidence.
- Preferred experience with agentic workflow frameworks, AI coding tools, coding models, vector databases, graph stores, code indexing, APIs, observability, and evaluation dashboards.

Benefits

- Hybrid remote/on-site work model with flexible working hours.
- International, dynamic, and collaborative work environment.
- Customized training through Coursera, weekly English and German language classes, international mentoring sessions, and Experience Days.
- Versátil compensation plan including health insurance, meal vouchers, childcare, and transport benefits.
- Telemedicine, life and accident insurance, social fund, and free specialist medical, legal, and wellness services.
- 26+ working days of vacation per year and 100% salary coverage during medical leave.

📌 AI SWE (España)
🏢 T-Systems Iberia
📍 España