Agentic AI Engineer

Role

Job Description

• Apply agentic AI fundamentals including goal definition, planning, reasoning, task decomposition, and autonomous action loops.
• Design and build LLM-based agentic workflows with tool calling, state management, memory, and single-agent or multi-agent orchestration.
• Use agent frameworks and patterns for routing, workflows, and agent coordination.
• Integrate tools and contextual data through Model Context Protocol servers.
• Build RAG pipelines and grounding strategies for enterprise knowledge sources.
• Implement AgentOps observability, monitoring, alerts, traces, and feedback loops.
• Deploy agentic systems at scale using cloud or platform engineering, containers, Kubernetes or OpenShift, CI/CD, performance tuning, and secure operations.
• Design responsible-AI guardrails including human-in-the-loop controls and safe tool access.

Technical Requirements

• Strong understanding of agentic AI fundamentals is required.
• LLM workflow design experience covering tool calling, state, memory, and orchestration is required.
• Agent-framework experience, including LangChain-based frameworks or equivalents, is required.
• Model Context Protocol proficiency is required.
• RAG pipeline and enterprise grounding experience is required.