Dynatrace's growth is increasingly tied to deep, co-engineered partnerships with the three hyperscalers and with the IDE and AI-tooling vendors developers actually use day-to-day. Recent integrations show that hyperscalers and IDE providers are no longer just deployment targets but co-development partners. The Model Context Protocol (MCP) has become the connective tissue: Dynatrace ships MCP servers so that Claude, Cursor, VS Code, JetBrains, Kiro, and other AI-assisted IDEs can query observability data natively. At the same time, customer workloads are shifting from traditional services to agentic AI systems that need a fundamentally new kind of observability.
This role sits at that intersection. You will build the product code that makes Dynatrace work seamlessly with hyperscaler AI services and with the AI-native IDEs developers use to build on top of them, in close technical collaboration with engineering counterparts at AWS, Microsoft, Google, Anthropic, GitHub, and Cursor.
The work is shipping code — APIs, agents, integrations, MCP servers, IDE extensions, telemetry pipelines — with partner engineers in the room.
What you will do
- Design and build integrations between Dynatrace and hyperscaler AI / observability services
- Build and maintain Dynatrace's Model Context Protocol (MCP) servers so AI assistants and agents can query problems, traces, logs, and Davis insights as first-class tools — and contribute upstream to the MCP spec where it matters.
- Co-develop with IDE providers (Anthropic / Claude Code, GitHub Copilot, JetBrains AI, Cursor, Windsurf, AWS Kiro, Gemini CLI) so Dynatrace observability shows up where developers already work — plugins, extensions, slash commands, MCP integrations.
- Co-develop with partner engineering teams at AWS, Microsoft, Google, and IDE vendors — joint design docs, shared backlogs, paired debugging across org boundaries.
- Extend Dynatrace's OneAgent and OpenTelemetry pipelines to capture traces, metrics, and evaluations from agentic AI workloads (tool calls, prompt chains, model latency, hallucination signals).
- Contribute to launch-partner integrations — being one of the first observability providers shipping against a new hyperscaler or IDE-vendor service requires fast iteration against pre-GA APIs.
- Own a slice of the partner-facing SDK, MCP server, or IDE-extension surface end-to-end: code, tests, docs, marketplace listing, on-call.
- Represent Dynatrace engineering in technical reviews with partners; translate Dynatrace's Davis AI and causal-AI capabilities into terms partner engineers care about.
- Mentor other engineers and raise the bar on how the team works across org boundaries.
Engineering foundation
- 5+ years of 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).
- 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.
- 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.
Dynatrace provides equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic. We actively foster an inclusive workplace that celebrates differences and promotes accessibility, collaboration, and growth for all.
