AI SDLC Lead Engineer (m/f/d)

Job Description Key responsibilities

Define and lead AI-assisted SDLC patterns for repository intake, code exploration, service mapping, build diagnosis, documentation, and engineering evidence generation. Guideanalysis 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 modelsoperatedthrough approved controls. Agentic and SDLC workflow components such asLangGraph, 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 orsystemslanguage 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 Whatdoweofferyou? Workenvironment&flexibility International,dynamicandcollaborativeenvironment. T-Social: socialinitiatives(sports,community,health, ...). Hybridworkmodel(remote/on-site). Flexibleworkinghours. Growth&development Customizedtraining:accesstoCourseratolearnwhateveryouwant,wheneveryouwant. Weeklylanguageclasses(English & German). InternationalMentoringSessions&ExperienceDays. Compensation&benefits Flexiblecompensationplan (healthinsurance,mealvouchers,childcare,transport). Telemedicine. Lifeandaccidentinsurance. Socialfund. Wellbeing& time off 26+workingdaysofvacationperyear. Freeaccesstospecialistservices(medical, legal,wellness). 100%salarycoverageduringmedicalleave. 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.

Your Task

This role focuses on defining and leading AI-assisted software development lifecycle patterns and guiding the analysis of OpenStack-derived control-plane services. The position involves evaluating and operationalizing AI development platforms, establishing quality controls for AI-generated outputs, and coaching engineering teams on effective AI tool usage.

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

• Work with AI development environments such as Cursor, Windsurf, Claude Code, Continue, Cline, or VS Code-based extensions connected to enterprise-approved model endpoints

• Utilize 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

• Leverage agentic and SDLC workflow components such as LangGraph, OpenAI Agents SDK, AutoGen, LlamaIndex, RAG pipelines, evaluation loops, and structured tool-calling patterns

• Operate within engineering environments including GitHub Enterprise, GitLab, Jenkins, ArgoCD, Helm, Docker, Kubernetes, private package registries, and terminal-native automation workflows

Your Profile

We are seeking a highly experienced AI-Assisted Engineering Lead with deep expertise in software engineering, AI coding tools, and platform architecture. The ideal candidate will have extensive hands-on experience with AI development platforms, coding agents, and LLM-enabled workflows, combined with strong technical skills in multiple programming languages and cloud-native technologies.

Must Have Skills

• 8+ years in software engineering, platform engineering, or technical architecture roles

• Proven ownership of complex engineering workstreams

• Strong hands-on coding skills in Python

• Proficiency in 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

• Experience with AI coding agents for technical documentation

• Experience with AI coding agents for engineering acceleration

• Good understanding of OpenStack-derived cloud software architectures

• Knowledge of modular service decomposition

• Experience with CI/CD

• Experience with Kubernetes-based delivery

• Knowledge of platform operations

• Ability to lead senior engineers in ambiguous environments

• Ability to challenge AI outputs

• Ability to convert incomplete evidence into structured, actionable engineering decisions

• Comfortable working in high-accountability, confidentiality-sensitive enterprise programs

• Experience working with auditability, traceability, and sovereignty constraints

• Familiarity with AI development environments such as Cursor, Windsurf, Claude Code, Continue, Cline, or VS Code-based extensions

• Knowledge of open-source, open-weight, or Chinese coding-capable models such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or similar models

• Experience with agentic and SDLC workflow components such as LangGraph, OpenAI Agents SDK, AutoGen, LlamaIndex, RAG pipelines, evaluation loops, and structured tool-calling patterns

• Experience with engineering environments including GitHub Enterprise, GitLab, Jenkins, ArgoCD, Helm, Docker, Kubernetes, private package registries, and terminal-native automation workflows