Note: The job is a remote job and is open to candidates in USA. Dice is seeking an experienced Agentic AI Engineer with strong expertise in Agentic AI frameworks and Dynatrace Intelligence Platform. The ideal candidate will design and implement intelligent autonomous agents, orchestrate AI-driven workflows, and integrate advanced AI capabilities for real-time monitoring and operational automation.

Responsibilities

• Design and implement intelligent agent-based workflows using LangChain, LangGraph, and related Agentic AI frameworks
• Develop autonomous AI agents to automate operational processes, runbooks, incident response, and self-healing systems
• Integrate AI agents with the Dynatrace Intelligence Platform, leveraging Grail Data Lake and Smarts cape Dependency Mapping for contextual intelligence
• Architect, develop, and optimize advanced Retrieval-Augmented Generation (RAG) pipelines
• Build and manage multi-agent collaboration frameworks for complex operational use cases
• Utilize Dynatrace AI Observability to monitor agent interactions, execution traces, prompt performance, and operational costs
• Implement governance controls, approval workflows, fallback mechanisms, and human-in-the-loop safeguards
• Establish secure, compliant, and auditable AI operational frameworks
• Collaborate with Site Reliability Engineers (SREs), Developers, and Operations teams to identify operational challenges and implement AI-driven solutions
• Continuously improve AI agent performance, reliability, scalability, and observability
• Support deployment, monitoring, troubleshooting, and optimization of production AI systems

Skills

• Strong experience with Agentic AI Frameworks (LangChain, LangGraph)
• Experience designing and implementing AI Agents and autonomous workflows
• Hands-on expertise with Dynatrace Platform Integration
• Experience with Dynatrace Grail Data Lake
• Knowledge of Dynatrace Smartscape Dependency Mapping
• Strong experience building Retrieval-Augmented Generation (RAG) solutions
• Experience implementing Multi-Agent Architectures
• Knowledge of AI Observability, tracing, monitoring, and prompt auditing
• Experience implementing governance, compliance, and security controls for AI systems
• Understanding of distributed systems, automation, and operational intelligence
• Experience working with DevOps, SRE, or Operations teams
• Strong problem-solving and troubleshooting abilities
• Experience with enterprise AI automation and self-healing systems
• Knowledge of Generative AI, Large Language Models (LLMs), and prompt engineering
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
• Familiarity with MLOps and AI deployment best practices
• Experience integrating AI solutions within enterprise monitoring and observability ecosystems
• Prior experience supporting large-scale production environments

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