comparison
stennir vs hiring an in-house ai engineer — which makes sense when?
hiring a senior ai engineer in-house is the most honest competitor to an ai consultancy engagement, by roi math. the right answer depends on how many ai projects you'll sustain per year, your tolerance for recruiting cycles, and whether your existing team can absorb the work between projects.
head-to-head
the differences, named.
| criterion | stennir | hiring in-house (senior ai engineer) |
|---|---|---|
| time to first shipped tool | weeks (engagement starts after a discovery call and signed scope) | months (write the jd, recruit, interview, notice period, onboard, then start) |
| breadth of skills | senior team with specialist depth across data, ml, infra, ux, ops | one person's depth — strong somewhere, lighter elsewhere |
| on-cost | the engagement covers the scope; no benefits, manager time, tools, or recruiting cost | salary + benefits + equity + manager time + tools + insurance + recruiter fees |
| between projects | engagement ends cleanly; resume when the next scope is ready | the hire is idle, working on other things, or leaving — overhead continues |
| governance | shipped with the engagement (policy, audit, rollback plan included) | depends on the hire's experience — often built ad-hoc |
| scaling the work | add a second engagement; the team scales with you | hire another, repeat the recruiting cycle for each |
| long-term knowledge accrual | documented in runbooks + handover; ongoing knowledge stays with the stennir team | in-house ownership — the hire learns your business deeply and stays (if they stay) |
when hiring in-house wins
you'll sustain three or more ai projects per year. you have an existing engineering organization that can absorb the hire between projects (so they're not idle). you need someone who is also a leader or manager — recruiting future engineers, owning the org's ai strategy, building internal credibility. the work has a long enough horizon that twelve to eighteen months of onboarding pays back.
when stennir wins
you have one or two ai projects this year, not a sustained pipeline. you don't have an engineering organization to absorb a senior hire (so they'd sit idle or own work outside their craft). you need the work to ship in weeks, not months. you want governance shipped with the implementation, not built after the fact.
the hybrid that often beats both
ship the first one (or two) with stennir — fast, with governance, with a runbook your team can read. then hire in-house once you have a real understanding of the scope and shape of the work the org will do at scale. the hire's first quarter is then operating a working system, not building one from a blank page.
the hybrid also de-risks the hire: you've already learned what good looks like at your org, so the jd is sharper and the interview signal is better.
the honest case for a fte
the strongest argument for in-house is long-term knowledge accrual. someone who works at your company for years learns the business in a way a consulting team can't replicate in a quarter. if your roadmap is dense and the work isn't one-shot, that compounds. we don't dispute this — if the math is right, hire.
we are
honest about when an in-house hire beats a consultancy engagement.
we aren't
an evergreen vendor. when an in-house team is the right answer, the right answer is an in-house team.
faq
questions buyers ask.
next step
still comparing? talk it through with us.
30 minutes. we'll write down what we'd recommend — even if another option is the better fit. specifics on shape, scope, and timing come out of the call.
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