Job ID: 744000142834900AI SWE / Code Quality Validation Engineer (m/f/d)GranadaProfessionalRegularT-Systems IberiaYour TaskThis role focuses on analyzing repositories and codebases for maintainability, security risks, and technical debt while leveraging AI coding agents to accelerate code review and validation processes. You will support due diligence activities by running quality and security scanning tools, validating build and release processes, and creating comprehensive evidence packs that document findings and risk assessments.

Key Responsibilities
Analyse repositories for maintainability, dependency risks, hidden coupling, insecure patterns, build fragility, licensing signals, and documentation gaps relevant to due diligenceUse AI coding agents to accelerate code review preparation, vulnerability explanation, remediation proposal drafting, and technical debt clustering across large codebasesRun and interpret quality, dependency, secret, container, and infrastructure scanning tools while documenting false positives, residual risks, and required expert reviewSupport reproducible build and release validation by analysing logs, pipeline definitions, container images, package sources, artefact flows, and configuration assumptionsCreate evidence packs that link findings to code locations, tool results, reviewer decisions, risk severity, mitigation options, and readiness implicationsCollaborate with security, DevOps, architecture, and test specialists to ensure AI-assisted validation results are actionable and aligned with enterprise assurance expectationsTools and PlatformsYou will work with AI coding and review environments such as Cursor, Windsurf, Claude Code, Continue, Cline, Aider, or VS Code-based assistants connected to approved model endpoints.



You will utilize open-source or Chinese coding-capable models such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or similar internally hosted models. Quality and security tooling includes SonarQube, Semgrep, Trivy, GitGuardian, Syft, Grype, dependency-check, Falco, SBOM tooling, and container/image scanners. Engineering environments include GitLab, GitHub Enterprise, Jenkins, Kubernetes, Helm, Docker, ArgoCD, package registries, Python tooling, and log analysis workflows.

Your Profile
We are seeking a highly skilled Software Engineer with extensive experience in secure development, DevSecOps, and platform engineering, combined with strong expertise in AI-assisted code review, vulnerability analysis, and software supply-chain security validation.
Must Have Skills5+ years of experience in software engineering, secure development, DevSecOps, platform engineering, or quality-focused engineering rolesStrong Python programming skillsPractical experience in at least one backend or systems language such as Go, Java, C, C++, or RustHands-on experience with code reviewHands-on experience with vulnerability triageHands-on experience with dependency analysisHands-on experience with CI/CD inspectionHands-on experience with container securityHands-on experience with software supply-chain evidence generationPractical experience using AI coding assistants for code understanding, documentation, remediation proposals, test generation,



or large-repository review accelerationAbility to analyze repositories for maintainability, dependency risks, hidden coupling, insecure patterns, build fragility, licensing signals, and documentation gaps relevant to due diligenceAbility to use AI coding agents to accelerate code review preparation, vulnerability explanation, remediation proposal drafting, and technical debt clustering across large codebasesAbility to run and interpret quality, dependency, secret, container, and infrastructure scanning tools while documenting false positives, residual risks, and required expert reviewAbility to support reproducible build and release validation by analyzing logs, pipeline definitions, container images, package sources, artifact flows, and configuration assumptionsAbility to create evidence packs that link findings to code locations, tool results, reviewer decisions, risk severity, mitigation options, and readiness implicationsAbility to collaborate with security, DevOps, architecture, and test specialists to ensure AI-assisted validation results are actionable and aligned with enterprise assurance expectationsComfortable producing concise, evidence-backed findings in high-accountability environments where confidentiality, auditability, and reviewer judgement are essentialExperience with AI coding and review environments such as Cursor, Windsurf, Claude Code, Continue, Cline, Aider, or VS Code-based assistants connected to approved model endpointsExperience with open-source or Chinese coding-capable models such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or similar internally hosted modelsExperience with quality and security tooling such as SonarQube, Semgrep, Trivy, GitGuardian, Syft, G

📌 Ai Swe (Granada)
🏢 Telekom
📍 Granada