EmergingTool-using agents and workflow orchestrationPart of The agent workforce

AI Agent Manager

Also called Agent Operator · Agent Supervisor · AI Ops Manager

An AI Agent Manager assigns work to AI agents, reviews what they produce, handles the exceptions and tunes the workflow. They make agents dependable enough to carry real business tasks, not just demos.

What they do

They decide which tasks go to an agent and which stay with people. They write clear instructions, set what each agent may and may not do, and check the output against what the business needs. When an agent fails or hits something odd, they step in, work out why and fix the cause. They watch queues, error patterns and cost per task. They adjust prompts, tool access, handoffs and review steps. They also tell the team what the agents can be trusted with this week, and what they cannot.

What a strong hire delivers

In the first months, a strong hire gets one or two real workflows running through agents with named permissions and a clear review step. They set up a simple way to see failures and exceptions. They cut the manual effort on those workflows without raising error rates. They leave behind written rules for what agents may do and when a person takes over.

How you can tell they are good

Ask them to walk through a workflow they ran with agents. Listen for specifics: what they handed over, what went wrong, how they found the cause, what they changed. Ask how they decided an agent's output was good enough. Strong people talk about permissions, evaluation and edge cases. Be wary of anyone who only talks about prompts or speed.

Why it is hard to fill

The title is new and the work often sits inside other jobs, so candidates rarely call themselves this. Most are application engineers, automation specialists or operations leads who drifted into it. The mix is awkward: they need operational judgement, a testing mindset and enough technical skill to work with tools and security limits. Few have all three, so expect to assess potential as well as history.

Where to find them

Look at application engineers, workflow automation builders and systems integrators who now supervise agents as part of the job. Operations and QA people in finance, support, logistics or compliance teams are another source, especially those who built internal automations. Enterprises and smaller businesses are both producing them, often without a formal title. Check what they actually run today.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Agent Manager

  1. Describe a workflow where you gave work to an agent. What did you keep for people, and why?

    A good answer draws a clear line based on risk, reversibility and cost of error. They name what they handed over and what they held back. Worry if they handed everything over, or cannot explain the split.

  2. How do you decide whether an agent's output is good enough to ship?

    Look for defined criteria, sampled review, test cases and tracking over time. They should separate checking one output from measuring a workflow. Worry about gut feel, or review that stops once things look fine.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are building agents into how our teams get work done, and we need someone to run them day to day. You will decide what agents handle, check what they produce, deal with what goes wrong and keep improving the workflows. We want someone practical, careful and comfortable with both operations and technology.

What you will do

  • Assign tasks to agents and decide which work stays with people
  • Define the tools and permissions each agent may use
  • Review agent output and track quality against agreed measures
  • Investigate failures and exceptions and fix the underlying cause
  • Tune prompts, handoffs and review steps to improve results and cost
  • Document how each workflow runs and when to escalate
  • Report plainly to the team on what agents can and cannot be trusted with

What you will bring

  • Has run or built automated or agent-based workflows that handled real work
  • Can show how they evaluated agent output and acted on the findings
  • Comfortable connecting agents to tools, APIs and internal systems
  • Understands access control and the risks of giving agents permissions
  • Strong operational judgement about risk, escalation and handoffs
  • Writes clear instructions and documentation others can follow

Nice to have

  • Background in application engineering or systems integration
  • Experience in QA or testing
  • Domain knowledge in an area such as finance, support or logistics

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Agent orchestrationWorkingCoordinate tool-using agent execution
  • Tool and protocol integrationWorkingConnect models to external data and capabilities
  • Security engineeringWorkingProtect systems, identities and sensitive assets
  • Model evaluationWorkingMeasure capability and failure modes credibly

Other roles in tool-using agents and workflow orchestration

Hiring nowAI Agent EngineerAn AI Agent Engineer builds software agents that take real actions through tools they are explicitly permitted to use. They turn model capability…Hiring nowAgent Tool Integration EngineerAn Agent Tool Integration Engineer connects AI agents to outside systems through tightly scoped interfaces. They make sure agents act only where…EmergingAgent Workflow ArchitectAn Agent Workflow Architect decides which tasks go to agents, which stay with people, and where approvals sit. It matters because agents that act…EmergingComputer-Use Agent EngineerA Computer-Use Agent Engineer builds agents that operate real application interfaces, clicking, typing and reading screens, within firm limits. They…EmergingAgent Memory and Personalisation EngineerBuilds the memory, user models and personalisation layers that let an agent remember people across sessions and act on it. It matters because an…

Related roles in other families

EmergingMulti-Agent Systems ResearcherMulti-agent coordination and economicsA Multi-Agent Systems Researcher studies how several AI agents behave when they work together, and builds methods and benchmarks to make that…EmergingAgent Coordination EngineerMulti-agent coordination and economicsAn Agent Coordination Engineer builds the layer that lets several AI agents hand work to each other, share state and settle conflicts. It matters…EmergingMulti-Agent Evaluation ScientistMulti-agent coordination and economicsA Multi-Agent Evaluation Scientist measures how groups of AI agents behave together and designs tests that expose collusion, cascades and…EmergingAgent Market Mechanism ResearcherMulti-agent coordination and economicsThis person designs and tests the rules that govern how AI agents trade, bid and share resources in bounded simulated markets. It matters because…

How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

← Tool-using agents and workflow orchestrationAll new job families

Start a search

Hiring an AI Agent Manager?

Tell us the work. We find the people already doing it, whatever their job title says, and you meet them already interviewed for your role.