AI Engineering Workflow Developer (mf/d)

T-Systems Iberia; Valencia; Híbrido; EUR 42.000 - 68.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Meal vouchers

Telemedicine

Life and accident insurance

Social fund

24–26 vacation days

Descripción de la vacante

T-Systems Iberia in Valencia is seeking a software engineer to develop and maintain AI-assisted tooling for repository indexing, code summarization, and documentation generation. You will collaborate with senior engineers to configure AI environments and test prompts, aiming to improve SDLC workflows.

Ideal candidates have 2–4 years in software engineering, solid Python skills, hands-on experience with Git, Docker and Kubernetes, and a curiosity-driven approach to learn new AI models and tooling.

Formación

• 2–4 years in software engineering, DevOps automation, data engineering, AI tooling, or platform-adjacent development roles.
• Good Python skills and willingness to work across APIs, scripting, developer tooling, documentation, tests, and lightweight automation services.
• Hands-on familiarity with AI coding assistants, prompt engineering, LLM APIs, local model experimentation, or RAG-style development is strongly preferred.
• Basic understanding of Git, CI/CD, Linux, containers, cloud platforms, and software architecture documentation, with readiness to deepen OpenStack knowledge.
• Careful working style with good documentation habits, curiosity, and ability to elevate unclear findings instead of over-trusting AI-generated answers.
• Comfortable working in a confidential enterprise environment where learning speed, quality discipline, and structured communication are important.

Responsabilidades

• Implement and maintain small AI-assisted engineering utilities for repository indexing, code summarization, dependency extraction, log parsing, and documentation generation.
• Support senior engineers in configuring AI development environments, testing prompts, comparing model outputs, and documenting repeatable SDLC usage patterns.
• Create scripts and lightweight services that connect Git repositories, CI/CD logs, issue trackers, documentation stores, and internal model endpoints.
• Help prepare handover materials including codebase summaries, service notes, build observations, glossary entries, and structured evidence templates.
• Test open-source, open-weight, and Chinese coding models in approved environments and document strengths, limitations, risks, and practical usage guidance.
• Participate in reviews with senior engineers to validate AI-generated outputs, correct inaccuracies, and improve workflow quality over time.

Conocimientos

Python

Prompt engineering

AI tooling

Documentation

Curiosity & learning

Herramientas

Git

Docker

Kubernetes

Jenkins CI/CD

Linux

Descripción del empleo

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.

Job Description

Key responsibilities

• Implement and maintain small AI-assisted engineering utilities for repository indexing, code summarization, dependency extraction, log parsing, and documentation generation.
• Support senior engineers in configuring AI development environments, testing prompts, comparing model outputs, and documenting repeatable SDLC usage patterns.
• Create scripts and lightweight services that connect Git repositories, CI/CD logs, issue trackers, documentation stores, and internal model endpoints.
• Help prepare handover materials including codebase summaries, service notes, build observations, glossary entries, and structured evidence templates.
• Test open-source, open-weight, and Chinese coding models in approved environments and document strengths, limitations, risks, and practical usage guidance.
• Participate in reviews with senior engineers to validate AI-generated outputs, correct inaccuracies, and improve workflow quality over time.

Examples of market tools, models, and SDLC platforms expected

• AI development environments such as Cursor, Windsurf, Continue, Cline, Aider, Claude Code, or VS Code-based extensions configured for enterprise repositories.
• Model families used for coding support such as DeepSeek Coder, Qwen/Qwen-Coder, CodeGeeX, StarCoder, Code Llama, Mistral, or other internally approved models.
• Workflow and integration tooling such as Python, FastAPI, notebooks, LangChain, LlamaIndex, GitLab/GitHub APIs, Jenkins APIs, Markdown, and documentation automation.
• Supporting engineering tools such as Git, Docker, Kubernetes basics, Helm basics, Linux shells, package managers, log processing, and structured prompt repositories.

Qualifications

• 2-4 years in software engineering, DevOps automation, data engineering, AI tooling, or platform-adjacent development roles.
• Good Python skills and willingness to work across APIs, scripting, developer tooling, documentation, tests, and lightweight automation services.
• Hands-on familiarity with AI coding assistants, prompt engineering, LLM APIs, local model experimentation, or RAG-style development is strongly preferred.
• Basic understanding of Git, CI/CD, Linux, containers, cloud platforms, and software architecture documentation, with readiness to deepen OpenStack knowledge.
• Careful working style with good documentation habits, curiosity, and ability to elevate unclear findings instead of over-trusting AI-generated answers.
• Comfortable working in a confidential enterprise environment where learning speed, quality discipline, and structured communication are important.

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!

T-Systems Iberia will only process the CVs of candidates who meet the requirements specified for each offer.