AI Operations professionals are emerging as a bridge between technology, processes, and business

Startups are creating a new role that sits at the intersection of technology, operations, and strategy: the AI Operations professional, also known as AI Ops. Instead of developing artificial intelligence models from scratch, these professionals focus on integrating AI tools and agents into a company’s workflows.

Job postings published in 2026 by companies such as Squint, Broccoli AI, and Reindeer describe professionals responsible for building automations, creating internal agents, evaluating results, and identifying tasks that can be performed with AI.

What are the responsibilities of an AI Operations professional?

The work begins even before selecting a tool. The professional must understand how a team operates, identify repetitive activities, and assess where AI can be integrated.

For example, as an AI Operations Lead at Squint, responsibilities include creating agents and automated workflows for areas such as support and operations, as well as developing mechanisms to verify that these solutions are functioning correctly.

At Broccoli AI, the job description includes creating control panels, internal tools, and agents for sectors such as sales and customer service. The company also expects the professional to continuously monitor and improve the performance of these systems.

In practice, the daily routine may involve:

• mapping manual processes;
• identifying opportunities for automation;
• building agents and workflows using AI tools;
• testing the results generated by the systems;
• monitoring errors and performance;
• documenting processes;
• training teams to use the solutions;
• deciding which activities still require human intervention.

AI Operations is not the same as AI engineering

Although AI Operations professionals work directly with artificial intelligence, they do not necessarily need to develop language models or machine learning systems.

The distinction lies primarily in the type of problem being solved. An engineer may work on system architecture or model development. In contrast, an AI Operations professional seeks to understand how existing technology can be applied to a company’s daily operations.

For example, a startup may have a model capable of analyzing documents. The AI Operations professional can transform this capability into a workflow that receives files, extracts information, organizes the data, and sends the results to another system.

Why are startups creating this role?

The expansion of AI agents also increases the need to organize what happens after implementation. It is not enough to make a tool available; it is necessary to define where it will be used, how it will be evaluated, and when a person should intervene.

A recent job posting from Mercury illustrates this challenge, highlighting that AI projects can face difficulties precisely at the stage of converting a technological solution into an effective change in the way of working. The company is seeking a professional to work closely with teams and transform the potential of AI into measurable improvements.

At Reindeer, another early-stage startup, the AI Operations Engineer works on creating internal tools, automations, and agents for areas such as sales, marketing, customer service, and finance.

What skills are required?

Job postings show that the role combines knowledge that traditionally belonged to separate areas, such as technology and business.

The skills sought include:

AI knowledge: understanding language models, agents, automation, and the limitations of these tools.

Process vision: identifying bottlenecks and repetitive tasks that can be modified.

Data analysis: tracking metrics to verify whether an automation has actually delivered results.

Communication: interacting with technical teams and professionals from areas such as sales, marketing, finance, and customer service.

Building capacity: in some companies, the professional needs to create prototypes, integrations, and automations using AI tools and workflow platforms.

An AI Operations job posting in São Paulo also combines customer service, data analysis, AI assistant creation, and process automation, showing that the role can take different forms depending on the company.

A role that is still being defined

AI Operations is still not a profession with a standardized scope. The job postings analyzed use titles such as AI Operations Lead, AI Operations Manager, AI Ops Engineer, and AI Operations Specialist, and responsibilities vary between companies.

In some cases, the focus is on internal automations. In others, it involves implementation for clients, quality control, or technical infrastructure.

The common point is the attempt to transform artificial intelligence from an isolated tool into a part of work processes. Therefore, the role tends to combine technology, operations, and management skills, especially in companies that adopt agents and automations in different areas.