AI Platform Engineer

Company Description

As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries.

DT-ITS recieved the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.

Job Description

We are looking for a Senior AI Platform Engineer to build AI-powered automation for complex cloud engineering environments.

You will combine your platform engineering, software development and cloud expertise with modern Generative AI technologies to automate parts of the software development lifecycle (SDLC).

Your work will focus on building reusable AI-assisted workflows that help engineering teams understand large codebases, discover service dependencies, diagnose CI/CD failures, analyze cloud services and generate reliable technical documentation.

This is not a traditional data science or machine learning role. We are looking for an engineer who understands how modern software and cloud platforms work and can apply LLMs, RAG and AI agents to real engineering problems.

What you'll work on

You will design and build AI-powered engineering workflows such as:

• Analyzing large Git repositories and identifying service boundaries and dependencies
• Building AI agents that interact with source code, Git platforms, CI/CD systems and engineering tools
• Diagnosing build and deployment failures using source code, configuration and pipeline logs
• Creating RAG-based solutions for searching and understanding large codebases and technical documentation
• Automating the generation of architecture and engineering documentation
• Connecting LLMs to engineering systems through APIs and tool calling
• Building controlled agentic workflows with validation, retries, confidence checks and human approval steps
• Evaluating different LLMs and approaches for software engineering use cases
• Turning successful prototypes into reusable, maintainable and production-ready engineering solutions

You will work closely with cloud, platform and software engineers within the .