AI Engineering Workflow Developer for T Cloud Public (m/f/d)

Odmeňovanie

From 1 150 EUR/month

Final salary is negotiable.

We are offering base salary depending on seniority level and previous experience of candidate. In addition to base salary we provide variable part and other financial benefits.

Náplň práce

Support engineering teams by building, testing, and maintaining AI-assisted development workflows that accelerate code understanding, documentation, build triage, and handover preparation for cloud software and platform work packages.

This more junior position supports senior AI software engineering and platform specialists by implementing workflow utilities, prompt packs, repository analysis scripts, documentation helpers, and integration adapters. The candidate should be eager to learn enterprise cloud platforms, AI development tooling, and disciplined software handover practices.

Čo budeš robiť

• 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 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 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.

Očakávania

• 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 CI/CD, Linux, containers, cloud platforms, and software architecture documentation, with readiness to deepen cloud platform knowledge.
• Careful working style with good documentation habits, curiosity, and ability to escalate unclear findings instead of over-trusting AI-generated answers.