Hire an AI engineer, or bring in an outside team?
Hire an AI engineer when AI is core to your product, you have a steady backlog of things to build and a technical leader to manage the role. An outside team like Modern Thesis fits a non-tech company without a CTO that needs strategy, building, change management and upkeep, without recruiting and keeping one hard-to-find specialist.
What does it cost to hire an AI engineer?
More than the salary. Kore1's 2026 AI engineer salary guide puts mid-level base pay at $140,000 to $210,000.1 Add benefits, payroll taxes, recruiting fees and software. You will also be competing with technology companies for the same people, and a non-tech company usually has less to offer an engineer who wants to work with other engineers. None of this rules out a hire. It means the decision deserves a real budget and a clear plan for the role.
When is hiring the right choice?
Hiring is right when AI is part of what you sell, not only how you operate. It is also right when you have a steady backlog of things to build, more than a year of work you can already name, and a technical leader such as a CTO or head of engineering who can set priorities and review the code. Under those conditions, an employee builds knowledge inside the company that an outside team can't match. If that describes you, hire, and use outside help only where you get stuck.
What does one hire usually miss in a non-tech company?
Breadth. A return from AI takes several kinds of work: a map of how the process really runs, clean data, integrations, accuracy tests, staff training, aligned incentives and upkeep as models change. One person rarely covers all of it. In a company without a technical leader, that person also has no one to review their work or protect their time. If they leave, the systems can lose their only maintainer.
How does hiring compare with an outside team?
| Hire an AI engineer | Outside AI team | |
|---|---|---|
| Cost | Salary, benefits, recruiting and tools, fixed each year | Fees priced to the scope, which can grow or shrink with the work |
| Time to start | After recruiting and onboarding | When the engagement starts |
| Skills covered | One person's strengths | Strategy, engineering, change management and upkeep across a team |
| Management needed | A technical leader to set priorities and review work | Managed by the partner, with an agreed amount of your time |
| If someone leaves | Systems may lose their only maintainer | The partner covers continuity |
| Knowledge | Builds inside the company | Stays in house only through documentation and training, so ask for both |
| Best fit | AI is core to the product, with a backlog and a technical leader | Non-tech company, no CTO, several workflows to change |
Are outside teams more likely to get AI into production?
The research leans that way, with caveats. MIT NANDA's 2025 study found that AI work done with outside partners reached deployment about 67% of the time, against about 33% for internal builds.2 The figures are self-reported, and the authors note that companies choosing partners may differ in other ways. RSM's 2025 middle market AI survey found that 70% of respondents said they needed outside help to get the most out of their AI solutions.3 Neither study says an outside team is always right. They do suggest that building alone is harder than most companies expect.
If you do hire, what sets the role up to succeed?
Give the role a manager who can judge technical work, even part time. Hand the new engineer a short list of workflows with a measured baseline, so they build where the return is clear. Keep every account and code repository in the company's name. Budget separately for staff training, since adoption is rarely an engineer's strength or job. And decide in advance who covers the systems when your engineer takes a vacation or moves on.
Can you start with an outside team and hire later?
Yes, and for many companies it is the sensible path. An outside team can find where AI pays, build the first systems and prove the return. Once you have running systems and a backlog worth a full-time salary, you hire into a defined role with real work to maintain. Make the handoff part of the plan from the start: company-owned accounts, written documentation and code your new hire can read.
How Modern Thesis handles this
Modern Thesis works as the outside team for non-tech companies, typically with $10 million or more in annual revenue. Jim Coleman leads strategy. Our AI specialists and Forward Deployed Engineers lead the build, and change management is part of every engagement. We start with a strategic assessment that measures time, cost and error rates on your key workflows, then build, then stay with no end date. You own the code, accounts, data and documentation, so a future hire can pick up the work. If hiring is the better answer for you, we'll say so.
Questions
How much does it cost to hire an AI engineer?
Kore1's 2026 AI engineer salary guide puts mid-level base pay, for three to five years of experience, at $140,000 to $210,000. Across all levels it reports $145,000 to $310,000 in base pay. Benefits, payroll taxes, recruiting fees and software come on top of salary. For a non-tech company, also count the cost of managing the role, since an engineer without a technical leader tends to drift toward whatever request arrived last.
Can our IT person or a junior developer handle AI for us?
They can handle part of it. A capable IT person can roll out licenses, set permissions and keep accounts secure, and a junior developer can build simple integrations. Choosing which workflows to change, designing checks for accuracy, training staff and maintaining systems as models change usually takes more experience. Give them a clear scope and a senior person to review their work, inside the company or outside it.
What happens to our AI systems if our engineer leaves?
That depends on what they left behind. If the code, accounts and documentation sit in company-owned systems and someone else understands them, a replacement can take over. If the knowledge lived in one person's head, systems tend to stall or break quietly. Whoever builds your AI, in house or outside, insist on company-owned accounts and written documentation from the first week.
Do we own the work if an outside team builds it?
You should, and you should get it in writing before work starts. Ask who holds the code, which accounts the systems run under, and what documentation you receive. At Modern Thesis the client owns its data, accounts, code and documentation, and our access is removed when an engagement ends. Treat vague answers on ownership as a reason to keep looking.