AI SWE / Agentic SDLC Workflow Engineer (mf/d/)

T-Systems Iberia

España

Presencial

EUR 70.000 - 100.000

Jornada completa

Hace 9 días

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Envía un currículum específico para el puesto de trabajo en cuestión de minutos.

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Flexible hours

Language classes

Meal vouchers

Health insurance

Descripción de la vacante

T-Systems Iberia in Spain is seeking an AI SWE / Agentic SDLC Workflow Engineer to design and implement AI-assisted workflows that analyze repositories, scan code, decompose services, and generate documentation. You will package prompts, tools, and model routing into repeatable accelerators and integrate them with Git platforms and CI/CD pipelines.

You will turn prototypes into reusable workflows with robust logging, clear interfaces, and maintainable configuration, while evaluating open-source

Formación

5+ years in software development, DevOps automation, platform engineering, or AI workflow implementation.
Strong hands-on Python and API integration experience.
Experience turning prototypes into reusable workflows with clear interfaces, logging, and error handling.
Good understanding of CI/CD, Git workflows, containers, Kubernetes, and modular cloud environments.
Strong written communication for workflow docs, evidence packs, and stakeholder guidance.
Ability to work in confidential settings and turn AI outputs into reliable engineering evidence.

Responsabilidades

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 accelerators.
Integrate AI workflows with Git platforms, CI/CD systems, documentation stores, issue trackers, and architecture repositories.
Create auditable workflow outputs with traceable sources, confidence indicators, and reviewer checks.
Experiment with open-source/open-weight models and Chinese coding models in approved environments for SDLC automation.
Support work-package leads by translating questions into structured AI-assisted workflows and deliverables.

Conocimientos

Python

API integration

Orchestration frameworks

RAG patterns

Tool calling

Evaluation loops

CI/CD

Git workflows

Containers

Kubernetes

Software architecture docs

Logging & error handling

Configuration & maintainability

Herramientas

VS Code integrations

Repo analysis tools

Descripción del empleo

AI SWE / Agentic SDLC Workflow Engineer (mf/d/)

Full-time

T‑Systems is part of the Deutsche Telekom Group, with around 30.000 employees worldwide. We create technology with purpose to generate a positive impact on society. We are looking for curious talent, eager to learn, take on challenges, and contribute ideas that transform our customers’ experience.

We trust people: we offer autonomy, continuous support, and a collaborative environment where you can grow without limits. We are one global team, guided by respect, integrity, and a passion for doing better every day.

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 thatremainauditable, 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 asLangGraph,AutoGen,CrewAI, OpenAI Agents SDK,LlamaIndexWorkflows, 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,OpenAPIwrappers, 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.

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