As an Intermediate Agentic AI Engineer, you will serve as the technical backbone for building and scaling our production-grade multi-agent platform. Working primarily with Python and modern orchestration frameworks like LangGraph, you will design a hierarchical multi-agent layer, implement dynamic context-loading mechanisms, and integrate standardized tool-calling interfaces to transition legacy workflows into fully autonomous systems.

This role is critical to optimizing our AI ecosystem's performance, token economics, and operational security. By establishing automated evaluation harnesses, robust observability stacks, and enterprise-grade security guardrails, your work will directly drive the reliability, safety, and scalable impact of high-performing AI agents across our organization.

Architect and deploy a hierarchical multi-agent workflow using LangGraph, successfully transitioning legacy single-prompt implementations into modular agentic systems.

Build domain-specific sub-agents featuring dynamic, on-demand context loading to significantly optimize latency and token economics.

Design and integrate scalable tool-calling capabilities and standardized connectors using the Model Context Protocol (MCP).

Optimize LLM observability, reasoning traces, and cost-tracking systems by setting up and managing LangFuse.

Lead the establishment of automated evaluation harnesses and regression testing suites using tools like PromptFlow or PromptFoo against benchmark datasets.

Collaborate on implementing strict security guardrails and access controls following OWASP Top 10 standards for LLM applications.

Intermediate Agentic AI Engineer

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Coderoad

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