What will help you succeed Engineering foundation

* Profound professional software engineering experience building and operating production backend systems. * Strong proficiency in at least one of Java, Go, Python, or TypeScript; able to ramp on a second within a quarter. * Designed and shipped public-facing or partner-facing APIs (REST and / or gRPC), including versioning, backwards compatibility, and SDK ergonomics.

Hyperscaler depth (at least one)

* Hands-on, production-grade experience with AWS, Azure, or GCP

• building against native SDKs, not just deploying to VMs.

* Concrete familiarity with the partner-relevant surface of that cloud:

AWS: Bedrock / AgentCore, Lambda, EKS, CloudWatch, AWS Marketplace, Partner Network (APN).

Azure: Azure OpenAI, AKS, Azure Monitor, SRE Agent, Azure Marketplace, MISA.

GCP: Vertex AI / Gemini, GKE, Cloud Operations, Google Cloud Marketplace, Partner Advantage.

Observability and AI workloads

* Working knowledge of observability primitives: metrics, logs, distributed tracing, OpenTelemetry instrumentation. * Understanding of how to instrument LLM and agentic-AI workloads: prompt / response capture, token usage, tool-call traces, evaluation signals, latency and cost attribution. * Comfortable reasoning about SLOs, error budgets, and incident response in customer-facing systems.

MCP and IDE-provider integration

* Practical experience with the Model Context Protocol (MCP)

• building MCP servers, clients, or both. Comfortable with stdio and HTTP transports, tool / resource / prompt primitives, auth, and the realities of running MCP in production.

* Built at least one IDE extension, plugin, or integration that real developers used

• for VS Code, JetBrains, Cursor, Claude Code, GitHub Copilot, Gemini CLI, Kiro, or similar.

* Understands the AI-assisted developer workflow end-to-end: how agents discover tools, how context windows fill up, how tool outputs get re-ranked, why a well-designed tool schema matters more than a clever prompt. * Can reason about trade-offs of agent-facing API design vs. human-facing API design (token cost, determinism, error surfacing, idempotency).

Why you will love being a Dynatracer * Dynatrace is a leader in unified observability and security. * We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. * Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. * You'll get to work at the forefront of innovation with Dynatrace Intelligence-the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next

• automatically.

* Over 50% of the Fortune 100 companies are current customers of Dynatrace.

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.

Apply now: https://www.dynatrace.com/careers/jobs/1400274500/