AI SWE Agentic SDLC Workflow Engineer (mfd)

Key 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 workflow outputs that remain auditable including traceable source references confidence indicators reviewer checkpoints and explicit assumptions. 
• Experiment with open-source open-weight and Chinese coding models in approved environments to compare usefulness for SDLC automation and handover tasks. 
• Support work-package leads by translating ambiguous engineering questions into structured AI-assisted workflows and validated deliverables. 

Examples of market tools models and SDLC platforms expected 

• Agentic workflow frameworks such as LangGraph AutoGen CrewAI OpenAI Agents SDK LlamaIndex Workflows Semantic Kernel or comparable orchestration stacks. 
• AI development platforms and editor integrations such as Cursor Windsurf Claude Code Continue Cline Aider or VS Code-compatible internal assistants. 
• Model families relevant to SDLC automation such as DeepSeek Coder Qwen/Qwen-Coder CodeGeeX StarCoder Code Llama Mistral or enterprise-hosted frontier models. 
• Supporting components including vector databases graph stores code indexing OpenAPI wrappers GitLab/GitHub APIs Jenkins APIs observability and evaluation dashboards. 

Qualifications :

• 5 years of engineering experience across software development DevOps automation platform engineering or AI workflow implementation. 
• Strong hands-on Python skills API integration experience and 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 discipline. 
• Good understanding of CI/CD Git workflows containers Kubernetes software architecture documentation and modular cloud software environments. 
• Strong written communication skills for creating workflow documentation evidence packs usage guidance and decision support for senior stakeholders. 
• Comfortable operating in ambiguous confidentiality-sensitive settings where AI outputs must be reviewed justified and converted into reliable engineering evidence. 

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 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.

Remote Work :

No

Employment Type :

Full-time