Full-time Hybrid https://www.dynatrace.com/careers/locations/linz/, https://www.dynatrace.com/careers/locations/vienna/, https://www.dynatrace.com/careers/locations/klagenfurt/, https://www.dynatrace.com/careers/locations/graz/, https://www.dynatrace.com/careers/locations/innsbruck/, https://www.dynatrace.com/careers/locations/hagenberg/, Austria https://www.dynatrace.com/careers/teams/engineering/ Experienced and Senior Job Id: 5365

Your role at Dynatrace Most AI developer tools operate without any knowledge of how software actually behaves in production. Dynatrace is in a unique position to change that.

We're looking for an engineer who lives at the intersection of open standards, distributed systems, and AI infrastructure. You will own the path that telemetry from AI workloads takes into Dynatrace

• from the moment an SDK emits a span in a customer's LLM application, through ingest, validation, and into the data model that powers our AI observability product.

This role sits inside Dynatrace's Engineering organization and works closely with product, design, and the platform teams that power Dynatrace's AI-observability stack.

Your responsibilities:

* Own OpenTelemetry ingest for AI workloads. Build and maintain the ingest path for OpenTelemetry traces, metrics, and logs emitted by GenAI applications, agents, and frameworks. Ensure it is robust, performant, and faithful to the spec. * Test and support integrations across the AI SDLC. Validate that popular AI SDKs, frameworks, and agent runtimes produce telemetry that flows cleanly into Dynatrace. Close the gaps you find

• in our ingest, in upstream instrumentation, or in the spec itself.

* Partner with the OneAgent team to align auto-instrumentation, context propagation, and runtime data collection for AI workloads, so customers get a coherent experience whether they instrument manually or rely on OneAgent. * Push GenAI semantic conventions forward across the industry by representing Dynatrace in the OpenTelemetry GenAI SIG. Propose, review, and drive consensus on semantic conventions for LLM calls, agents, tool use, evaluations, and emerging patterns. Help define what "good" AI telemetry looks like

• and make sure the standard reflects real production needs.

* Prototype quickly, run user feedback cycles, and ship to production * Collaborate with product and design to identify which developer problems are most worth solving. * Define technical strategy for the team's AI systems, set architectural direction, and mentor other engineers.

What will help you succeed * 5+ years (Senior) of professional software engineering experience * Demonstrated experience shipping production systems that use LLMs, including prompting, tool calling, evaluation, and iteration * Strong foundation in at least one of: developer tooling (IDEs, compilers, static analysis, code intelligence), AI/ML engineering, or large-scale distributed systems * Hands-on experience with agentic patterns: planning, tool use, retrieval, memory management * Hands-on experience with LLMs: prompt engineering, evaluation frameworks (e.g. LLM-as-a-judge, golden datasets, pairwise comparisons), or agent frameworks. * Ability to evaluate and critique AI-generated output. You understand when a model is wrong, not just that it is.

Compensation and Rewards * We offer attractive compensation packages and stock purchase options with numerous benefits and advantages. * Due to legal reasons, we are obliged to list a salary range for this position, which is €61,000 up to €92,000 gross per year based on full-time employment (38.5 h/week). We've listed the salary range for transparency, but if your experience and skills bring unique value, we'd still love to hear from you-please apply even if you're outside the range.

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