AI Agents Engineer
AI Agents Engineers design and build LLM-powered systems that can reason, plan, and act autonomously. Their daily English involves explaining agent loop design to stakeholders, documenting evaluation metrics, justifying safety decisions, and communicating system behaviour to non-technical audiences. This path builds the vocabulary for every layer of the agentic stack — from the ReAct pattern to production monitoring.
Topics covered
- Agent architecture
- Tool calling & function use
- Memory systems
- Evaluation & benchmarking
- Safety & guardrails
- Multi-agent coordination
Vocabulary spotlight
4 terms every AI Agents Engineer should know in English:
The iterative cycle of perceive → reason → act → observe that an AI agent executes to complete tasks
"The agent loop runs until the model signals task completion or a maximum step limit is reached."
A mechanism that allows LLMs to request execution of external functions (search, API calls, code) to gather information or take actions
"The agent resolved the query through three tool calling steps: search, fetch, and summarise."
A constraint or filter applied to agent inputs or outputs to prevent harmful, off-policy, or unexpected behaviour
"We added guardrails to block any agent action that would modify production data without confirmation."
An agent reasoning strategy that interleaves Reasoning and Acting steps with observations, enabling more reliable task completion than single-pass generation
"Switching from a single-shot prompt to a ReAct pattern reduced hallucination errors by 60%."
📚 Vocabulary Reference
Key terms organised by category for AI Agents Engineers:
Agent Architecture
Memory Systems
Safety & Evaluation
Production & Ops
Recommended exercises
Real-world scenarios you'll practise
- Explaining a multi-agent orchestrator design to a product manager who has no ML background
- Writing an evaluation report showing why the agent fails on edge-case inputs
- Justifying a human-in-the-loop checkpoint for irreversible agent actions in a design review
- Documenting guardrail logic in a post-incident report after an agent misfired