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Career route 4

Agent Systems Engineering

For roles like Agent Systems Engineer, Agentic AI Engineer, AI Agent Engineer

Engineer tool-using agent loops with explicit context, memory, orchestration, safety, evaluation, and production control.

14 lessons about 14 h of lessons Ends in a certificate Paid plans
Lesson checks passed0 of 14
Start: The Tool Interface - Why Agents Need Structured I/O

Is this route for you?

Do you want to engineer tool-using systems whose state, decisions, failures, and controls remain observable?

  • You enjoy reasoning about stateful systems, control flow, and failure recovery.
  • You want autonomy to be bounded by explicit contracts and evidence.
  • You prefer testable orchestration over opaque agent demos.

What you'll be able to do: Build on shared foundations to create agent systems with explicit tool contracts, state, safety boundaries, evaluation, and runtime evidence.

Start with

  • Complete the shared software engineering and AI foundations, or demonstrate equivalent working knowledge.
  • Be able to build an API-backed LLM application and read structured traces.
  • Understand basic testing, state management, and security boundaries.

The route

Common CoreBuild a typed tool surface and a bounded agent loop.
  1. 1The Tool Interface - Why Agents Need Structured I/OPhase 13: Tools and protocols · 45 min
  2. 2Tool Schema Design - Naming, Descriptions, Parameter ConstraintsPhase 13: Tools and protocols · 45 min
  3. 3MCP Fundamentals: Stateless Requests and JSON-RPCPhase 13: Tools and protocols · 55 min
  4. 4The Agent Loop: Observe, Think, ActPhase 14: Agent engineering · 1 h
  5. 5Tool Use and Function CallingPhase 14: Agent engineering · 1 h

You produce: A deterministic agent loop with typed tools, validation, stop conditions, and a transcript.

Role PracticeMake context, memory, state, and orchestration explicit and testable.
  1. 6Context Engineering: Windows, Budgets, Memory, and RetrievalPhase 11: LLM engineering and RAG · 1.5 h
  2. 7Agent Memory - Virtual Context and Memory PagingPhase 14: Agent engineering · 1.5 h
  3. 8Stateful Graph Orchestration - Durable Execution and CheckpointsPhase 14: Agent engineering · 1.5 h
  4. 9Orchestration Patterns: Supervisor, Swarm, HierarchicalPhase 14: Agent engineering · 1 h

You produce: A stateful workflow with a context budget, memory policy, checkpoints, and recovery paths.

Proof ProjectStress the system against realistic failures and unsafe inputs before release.
  1. 10Failure Modes: Why Agents BreakPhase 14: Agent engineering · 1 h
  2. 11Prompt Injection and the PVE DefensePhase 14: Agent engineering · 1.5 h
  3. 12Eval-Driven Agent DevelopmentPhase 14: Agent engineering · 1 h

You produce: An observable agent system with adversarial tests, trajectory evaluations, and explicit release gates.

Interview and Readiness EvidenceShow that the runtime can be operated from controls and trace evidence.
  1. 13Production Runtimes: Queue, Event, CronPhase 14: Agent engineering · 1 h
  2. 14Agent Observability: Langfuse, Phoenix, OpikPhase 14: Agent engineering · 45 min

You produce: A case study with architecture, failure evidence, runtime controls, traces, and justified tradeoffs.

Portfolio project: Observable Agent System

Build a bounded agent workflow whose tools, state, memory, failure behavior, and release evidence can be inspected.

  • A typed tool registry and agent loop
  • Explicit state and memory behavior
  • Failure and prompt injection tests
  • An agent evaluation suite
  • Runtime traces with stop, retry, and escalation evidence

You're ready when you can

  • Separate tool capability from agent decision policy.
  • Explain what enters context, what persists, and what expires.
  • Model state transitions and orchestration failure paths.
  • Test prompt injection, tool misuse, loops, and false completion claims.
  • Evaluate behavior from trajectories and operate it from traces.

What this route covers, honestly

Covered in depth
  • Tool contracts and agent loops
  • Context, memory, and state
  • Orchestration and failure modes
  • Agent safety, evaluation, and observability
Partly covered
  • Distributed agent systems
  • Human approval experience
  • Long-running workflow durability
Outside the course
  • Production fleet ownership
  • Provider-internal model control
  • Years of live on-call experience

Agent Systems Engineering career route certificate

Pass all 14 lesson checks on this route (0 done), then the 20-question route exam drawn from these lessons. The certificate lists every topic you covered and carries an ID anyone can verify.

Exam requirements

Completing this route shows that you can build and evaluate an observable agent system. It does not guarantee a role or prove experience operating a production agent fleet. This is a specialist overlay after shared foundations. MCP is one integration surface, not the definition of agent systems engineering, and the route does not replace distributed systems or live operations experience. The estimate covers lesson time only. Portfolio work and practice take additional time.