Automation

Why the automation engineer matters.

The tools can build a workflow. Someone still has to understand the work, connect the people, and make the result dependable.

Elijah EvynnPublished October 2, 2026 · 7 minute read

The short version

Automation needs an owner inside the organization.

An automation engineer finds work worth improving, maps how it actually moves across people and systems, builds the workflow, and stays accountable for how it performs after launch. The role matters because a working automation is an operating change, not just a technical artifact.

The best candidate is frequent, consequential work with a clear process owner.
The engineer owns discovery, design, delivery, exception handling, and improvement.
Measure the completed business job, not the number of automations built.

01 · The role

The hard part is knowing where automation belongs.

In his essay on the rise of the automation engineer, Jake Stauch argues that building an automation has become easier, while deciding what to automate and embedding it in a company remains difficult. That distinction is useful. A team can now connect apps or generate a workflow quickly. It still has to understand the exceptions, permissions, informal decisions, and handoffs that make the work real.

This guide is for operations and technology leaders deciding whether to build an automation function and what its first assignment should be.

The automation engineer is the person who holds those pieces together. They sit with the people doing the job, trace where information enters and leaves, choose the right boundary for automation, and design what happens when the ordinary path breaks. They work with process owners, IT, security, and the affected teams. The title can vary; the accountability should not.

The value is not the number of workflows shipped. It is how much dependable capacity the organization gains.

This is why the role cannot be reduced to a queue of requests for scripts. A request often describes the visible irritation, not the whole process. “Automatically approve access” sounds simple until different systems, approval rules, and employment changes are involved. The engineer has to find that context before choosing the tool.

02 · A practical example

Consider a new hire’s first day.

Imagine a growing company where HR records a start date, a manager requests access, IT creates accounts, and a specialist approves sensitive permissions. Automating only account creation saves a step. It can also create the wrong access if the role has changed or the approval has not happened.

An automation engineer would map the complete request: what event starts it, which data is authoritative, which access can follow a standard rule, who approves exceptions, and how the team learns that a step failed. They would build the routine path, keep sensitive decisions with the right person, and make the status visible to everyone who needs it. The same design should cover changes and offboarding, not only a smooth first day.

This is a hypothetical example, but the underlying engineering concern is concrete. Microsoft’s guidance on flow ownership and access notes that ownership choices affect stability, security, and compliance. A workflow that only its creator can run or maintain has not become an organizational capability.

03 · Organizational value

One role can improve the system around the work.

Capacity

Routine requests stop consuming the same attention every time. People can spend more of their day on cases that need judgment or relationship building.

Consistency

The normal path becomes explicit. Teams can see which steps are standard, which require approval, and where a handoff has stalled.

Learning

Exceptions reveal what the process does not yet handle. The engineer can use that evidence to improve the workflow instead of treating every failure as an isolated ticket.

Ownership

A named operator, documented access, and a maintenance path keep the automation useful when tools, policies, or people change.

The gains should be measured against the whole job. Count completed requests, time to resolution, exception rate, corrections, and the effort needed to keep the workflow running. Microsoft’s flow monitoring guidance likewise treats execution data as a way to find failures and improve performance. If AI makes decisions or takes actions in the workflow, NIST’s AI Risk Management Framework adds a useful standard for defined roles, human oversight, and ongoing review.

04 · Where to start

Give the engineer a workflow, an owner, and room to observe.

A company does not need to create a large automation department on day one. Start with a recurring process that crosses at least one meaningful handoff and has an operating leader willing to own the outcome. Let the engineer watch real cases before committing to a solution. Choose a first version with a clear start, end, and exception path.

01
Which repeated task consumes attention, and how often does it occur?
02
Who owns the outcome across every team the workflow touches?
03
Which steps follow stable rules, and which still require human judgment?
04
What will the team see when the workflow fails, and who will respond?
05
What evidence would show that the change improved the work?

Some organizations can grow this capability from an operations or IT team member who already understands the work. Others may need an embedded automation partner while they build internal ownership. In either case, the business must keep a process owner close to the engineer. Technical skill alone cannot decide which tradeoffs the organization should accept.

05 · Decision guide

Does your organization need this role now?

The answer depends on the work, not a headcount threshold. Use this comparison to identify the next capability the business actually lacks.

What you see	Better next move	Why
Repeated work crosses teams and systems, with delays or rework at the handoffs.	Assign an automation engineer alongside a business process owner.	Someone must map the whole job, build the routine path, and keep the exceptions visible.
People disagree about the policy or desired outcome.	Resolve process ownership first.	Code cannot settle a business decision the organization has not made.
A single stable task needs a simple connection between tools.	Let an existing platform or IT specialist implement it.	A dedicated role may be unnecessary for one contained workflow.
The workflow is clear but a critical system lacks a safe integration.	Bring in software or platform engineering.	The integration and security boundary may be the main engineering problem.

What to look for after the first release: a named owner, a visible exception path, a record of completed work, and a short list of improvements drawn from real use.

06 · Failure modes

Three ways to make the role ineffective.

01
Judging the engineer by workflow count. This rewards small, disconnected automations even when a cross-team process remains slow.
02
Keeping the engineer away from operators and decision makers. They cannot design around exceptions or adoption if all they receive is a ticket.
03
Launching without a process owner or maintenance plan. The automation may run, but no one can decide how it should change when the business changes.

These are design choices leaders can control. Give the role access to the work, authority to question a request, and an operating partner who owns the business outcome.

The point

Make automation a capability the company can keep.

Stauch’s argument points to a larger shift: as tools make workflow construction faster, the scarce skill moves toward understanding the organization. The automation engineer turns that understanding into systems people can trust, operate, and improve. For a growing company, that is how scattered experiments become lasting capacity.

For a deeper look at selecting the first opportunity, read what processes should be automated first and what makes an automation reliable.