Agentic Workflows: Design and implement intelligent agents and orchestrations (using frameworks like LangChain/LangGraph) to automate operations, runbooks, and selfhealing systems.
Dynatrace Integration: Integrate AI agents with the Dynatrace Intelligence platform, leveraging Grail data lakes and Smartscape dependency mapping for realtime context.
Model Orchestration & RAG: Architect and optimize advanced RAG pipelines and multiagent collaboration frameworks.
AI Observability: Use the Dynatrace AI Observability app to track interactions, trace executions, and audit prompts for performance and cost.
Governance & Safeguards: Establish approval mechanisms, fallback strategies, and humanintheloop controls to ensure secure and compliant autonomous operations.
Collaboration: Work closely with SREs, developers, and OPS teams to turn operational pain points into deployed AI solutions.
Required Qualifications
Experience: 8 10 years.
AI Tooling: Proficiency in Python and modern orchestration frameworks (e.g., LangGraph, AutoGen).
Dynatrace Exposure: Strong understanding of or ability to quickly learn the Dynatrace platform, including OneAgent, Davis deterministic AI, and Dynatrace API/SDK.
Cloud & DevOps: Familiarity with CI/CD pipelines, MLOps, and monitoring Kubernetes or microservices environments.
Problem-Solving: Strong reasoning skills with the ability to balance stochastic (GenAI) and deterministic (data/logic) decision-making in agentic systems