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# Senior AI Agent Software Engineer

- **Company:** Dynatrace GmbH
- **Location:** Linz, Austria
- **Experience:** Expert
- **Salary:** €61,000.0 - €76,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Automation of Tests, Unit Testing, Code Review, Software Debugging, Python (Programming Language), Software Engineering, Large Language Models, Prompt Engineering, Virtual Agents
- **Published:** September 25, 2026
- **Apply:** https://devjobs.at/job/1de343ceab57fd3202dddd3c17fa64b3

## About the Role

* Degree in Software Engineering or equivalent practical experience in software development., * Demonstrated ability to measure, evaluate, and prove agentic system quality through quantitative datasets and evaluation metrics rather than qualitative impressions.
 * Strong software engineering fundamentals, including continuous testing, production debugging, and full-service ownership.
 * Highly developed analytical, problem-solving, and collaborative skills to work effectively within an international engineering team., * To be successful in this role, you bring deep software development experience combined with a highly analytical and scientific approach to measuring AI system quality. We seek individuals who pair strong Go and Python foundations with hands-on, production-proven experience in orchestrating LLM APIs and agent loops.
 * Multiple years of professional, hands-on software engineering experience with deep expertise in Go and Python.
 * Direct experience building LLM-powered systems and agent loops, utilizing modern orchestration frameworks (like LangGraph), tool-calling, and structured-output APIs.

## Description

* We are looking for a practical, rigorous software engineer who is enthusiastic about turning LLM reasoning into safe, reliable, and tool-using agentic behaviors in production environments. You should be a builder at heart who enjoys engineering robust agent frameworks and evaluation pipelines rather than focusing purely on prompt design.
 * Design, build, and maintain our core Python agent layer, including LLM routing, tool-calling infrastructure, and structured-output retry logic that ensures dependability in production.
 * Design robust guardrails, input and output validation, and prompt-injection defences to mitigate hallucinations and prevent agents from deviating from their tasks.
 * Define and implement the datasets, metrics, and automated evaluation strategies necessary to measure and prove agent quality objectively across model updates and prompt modifications.
 * Drive high-level architectural decisions for our AI systems and actively participate in team code reviews, unit testing, and debugging efforts.


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