Senior AI Engineer APM Experiences at Datadog

The opportunityDatadogs APM Experiences team owns the core product experience for Application Performance Monitoring including distributed tracing service representation and more. Were building a new wave of AI-powered capabilities that help customers detect resolve and prevent performance issues this role you will lead endtoend development of LLM- and Agentbased features that can:Debug and investigate application performance issues down to the root cause as both a developer assistant and a fully autonomous agentProactively recommend performance and reliability-based optimizations to prevent the next incidentAutomatically create intelligent monitors and SLOs for the most important business flows and critical pathsThis is a highly productminded engineering role: youll work from problem discovery and UX all the way to reliable scalable production systems.What youll doShape AI experiences for APM. Design and ship LLM/agentic workflows that analyze traces metrics logs and other telemetry to generate diagnoses explanations and guided fixes.Own the full loop. Prototype quickly define success metrics and evals run experiments iterate and ultimately productionize for scale and reliability.Build robust agent systems. Develop tools retrieval and planning strategies and guardrails; manage prompts/evals; design fallbacks and humanintheloop paths.Integrate with Datadogs platform. Leverage surfaces like Trace Explorer Service Catalog monitors and workflows to deliver endtoend value in the APM UI.Partner deeply. Collaborate with PM Design and partner teams to build cohesive experiences.Raise the bar on engineering. Write performant maintainable backend code own services in production and improve reliability for highthroughput lowlatency data systems.Who you areProductminded engineer who ships AI to production4 years building backend or real-time ML systems; you value simplicity correctness and performanceProven experience delivering LLM/agent features to production (prompting tooling evals safety/guardrails)Comfortable owning user journeys iterating from prototype alpha GA and measuring impact with clear product metricsStrong ML / applied science fundamentalsSolid grasp of the ML lifecycle (task definition dataset collection modeling evaluation deployment iteration) and statistics (experiment design confidence intervals)Experience choosing/modeling the right technique for the job (e.g. anomaly detection ranking/recommendation NLP) and knowing when a heuristic beats a modelFluency with offline/online evals for AI systems; can build reliable golden sets and automatic regressionsDistributed systems & observability savvyExperience with microservices performance: tracing latency breakdowns concurrency and resiliency patternsProficient in Go Java or Python; strong API/service design; production ops (monitoring alerting oncall rotation)Nice to haveHandson with distributed tracing stacks (OpenTelemetry/Datadog APM) profilers and logs/metrics pipelinesExposure to planning/agent frameworks tooluse orchestration RAG and retrieval/indexing for observability dataFamiliarity with SLO/SLA practices and incident responseBenefits and Growth:Get to build tools for software engineers just like yourself. And use the tools we build to accelerate our development.Have a lot of influence on product direction and impact on the business.Work with skilled knowledgeable and kind teammates who are happy to teach and learn.Competitive global benefits.Continuous professional development.Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.Required Experience:Senior IC Key Skills APIs,C/C++,Computer Graphics,Go,React,Redux,Node.js,AWS,Library Services,Assembly,GraphQL,High Voltage Employment Type : Full Time Experience: years Vacancy: 1