Sharper Intake Questions Convert AI Search Speed Into Filled Requisitions

Entry-level technical roles tend to stall long before anyone opens a search. The hiring manager asks for years of experience the pay band can't buy, or describes the work in terms too general to identify who would succeed. AI has made the searching itself fast, so a requisition now reaches the recruiter carrying whatever went unresolved upstream. Recruiters now settle these issues during intake, in conversations with the hiring manager and with the people already doing the job.

Monia Smith is Senior Talent Acquisition Partner at NCR Atleos, where she recruits field technicians and engineers for a company that builds and services ATM networks. Smith runs full-cycle hiring across software engineering, product, data and analytics, information security, and field operations, and she built the company's first university recruiting program. She came into recruiting after working in probation and social work, a background that shapes how she reads an employment history and how she handles the gaps she uncovers.

"I want to know everything about the role. Does this position help solve any problems? What questions or issues is this role filling? How does this role help the company make money? I get that better understanding of who's successful," says Smith. The answers set her search criteria before she looks at a single resume. Field technicians are the roles Smith fills most often, where the gap between what a manager wants and what the budget covers opens widest.

Pay bands and experience asks

Field technicians at Smith's firm earn between $19 and $23 an hour, and the work involves travel, rotating schedules, and repairs across multiple sites. Slates for those roles come back rejected often enough that Smith stopped arguing the prior experience requirement in the abstract. Instead, she brings numbers into meetings and lets the manager draw the conclusion. "I have to educate the hiring manager. This is an entry level role. You can't request experience," Smith says. "I can show them the market data of other companies comparable to us, how much they're paying, and if they're providing training. Data helps me move decisions, especially with management. If you don't see it, you don't believe it."

The same band has to be sold to candidates who have been quoted more elsewhere. Smith reads the gaps and the asking rate together, then asks the candidate why their search has run this long. The answers run from family obligations to interviews that keep ending the same way. She coaches on that before making any case for the role. "I build a story of how to regain your life," Smith explains. "You haven't worked in 10 months. I can give you a position where you get training, you can get free educational resources. They can go to field three, they can go to a support engineer, and then they can go into a front or back end engineer without getting the four year degree."

Keywords from the crew

Hiring managers often describe roles from a distance, so Smith treats the intake as a starting point then goes deeper. She asks the manager for the names of the strongest people on the team, then talks to them directly. Referrals surface in those conversations, and Smith sends coffee and fast-food gift cards to the people who supply them. "In recruiting, you can't just talk to the hiring manager, especially hourly workers," Smith notes. "The workers that are leads tell me more information than a hiring manager because they work that job day to day. Their teams know, because they talk together."

Such conversations give Smith a set of search terms and a candid account of what makes the role difficult. She carries the candid account back to the manager as a fix. Roles that keep reopening usually reveal something about the job itself. "What are the good things about this position? What are the bad things about this position?" Smith asks. "If I find out enough information, of course I'm going to go to the manager. These are some things you can work on, so we don't need to hire for this role every other month."

Searching past the job boards

Smith uses AI to screen resumes, and the ranking it returns rests on what a document can show. A four-year employment gap reads as a date range to a screening tool and it's the first thing a manager wants explained. "AI doesn't take away that recruiter conversation and building that person up and speaking to the manager," Smith says. "He's going to want to know why he quit his job. What is his motivation? AI is not going to give you that."

AI took over the research that used to fill Smith's first week on a requisition. Now, she starts from the conditions of the job and sets the title aside. She lists what a field technician does across a week, then asks what other jobs run the same way. "For entry level roles, I need to know what roles are identifiable to the position I have," Smith explains. "These candidates go to different locations, they have to have critical thinking skills and they work on a schedule. Using AI, I would have like different examples, like Uber. Or pest control. It's a different industry, but the same type of work. They're answering calls from an app, they're sent work to them."

The same searches tell Smith which companies have recently cut staff. She works those lists first and runs the same approach on senior engineering roles, the ones furthest from her comfort zone. "You have to do that for high level engineering roles, because most of the time I still don't understand, but I need to better sell this role," Smith concludes. "In recruiting you can get all the information and the people that you need if you work at understanding that role or the industry to a certain degree. And then if you don't know, ask."