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AI Operations · Role

Agentic AI Engineer

The Agentic AI Engineer builds AI agents: systems that reason, use tools and act with autonomy. The most technical profile in the function.

What they do

  • Build agents that use tools and make decisions.
  • Design evaluation and guardrails so they don't go off the rails.
  • Ship agents to production with reliability and cost under control.

Skills it needs

Agent frameworks and LLM orchestrationProgramming (Python/TS)Agent evaluation and observabilityTool designSafety and guardrails

Salary by country and seniority

CountrySeniorityP25MedianP75
GermanyMid€65 860€66 220€66 580Estimation de sources publiques
GermanySenior€81 938€88 705€98 057Estimation de sources publiques
GermanyAll€98 057€103 705€109 352Estimation de sources publiques
SpainMid€36 000€41 000€48 000Estimation de sources publiques
SpainSenior€65 000€65 000€65 000Estimation de sources publiques
FranceMid€49 150€50 100€51 050Estimation de sources publiques
FranceAll€65 000€65 000€65 000Estimation de sources publiques
United KingdomMid€83 810€83 810€83 810Estimation de sources publiques
United KingdomSenior€132 218€134 385€136 553Estimation de sources publiques
ItalyMid€44 662€51 324€57 985Estimation de sources publiques
PortugalMid€40 500€40 500€40 500Estimation de sources publiques
PortugalSenior€56 733€56 733€56 733Estimation de sources publiques
United StatesMid€155 117€159 974€164 830Estimation de sources publiques
United StatesSenior€198 000€198 000€198 000Estimation de sources publiques
United StatesAll€148 720€168 444€174 125Estimation de sources publiques

Figures in euros, gross annual — each with its source.

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Also known as

The market uses several titles for the same role:

AI Agent EngineerAgent DeveloperApplied AI Engineer (agents)Autonomous Systems Engineer

How it changes by seniority

  • Junior Implements agents with tools and prompts against a given design.
  • Mid Designs evaluation and guardrails, and ships agents to production.
  • Senior Owns reliability and cost of critical agents; sets design patterns.
  • Lead Leads the agent team and the platform they’re built on.

When to hire

When you need custom agents, not a templated automation.

When not to

If your case is solved by an existing tool or a no-code flow.

Interview questions

  1. 1. You’re building an agent with access to the CRM and email. What limits do you set from the design?

    What to look for: Least-privilege per task, what it must NOT do, and brakes where it can do damage; security by design.

  2. 2. How do you choose the model for each step of the agent?

    What to look for: Model per task (cost vs. reliability), not the biggest for everything.

  3. 3. How do you know your agent is right before putting it in front of a customer?

    What to look for: Builds evals with real cases and a threshold; doesn’t trust "it works in my tests".

  4. 4. Your agent has to call tools and sometimes picks the wrong one. How do you control it?

    What to look for: Scaffolding with error handling, retries and clear autonomy limits.

Scorecard

  • Agent designDefines goal, tools, data and limits; knows what it must NOT be able to do.
  • Model choiceTunes model per task by cost and reliability, not defaulting to the largest.
  • EvaluationMeasures accuracy with real evals before production and on every change.
  • Security by designLeast-privilege and defence against misuse and injection, not bolted on at the end.

Red flags

  • Gives the agent broad access "so it can do anything" with no limits.
  • Ships with no way to measure whether it’s right.
  • Uses the most expensive model for everything and ignores cost per run.

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