AI SDLC Lead Engineer (mfd)

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 :

• 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 :

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