A country name is not hiring evidence. Neither is a university, a framework list, or a logo slide. If you are evaluating an engineering team — in Ukraine, Poland, Brazil, or three miles from your office — the only thing that predicts delivery is evidence from the specific people who will do the work.
That sounds obvious and almost nobody runs their process that way. The usual version compares hourly rates, checks a few references, and discovers in month four that nobody owns production.
Six areas, and what to actually ask
The architecture question is the one that separates seniority fastest. An engineer who names the option they rejected, and why, is reasoning about trade-offs. An engineer with one recommendation and no alternatives is reciting.
Replace the coding test with a paid slice of your actual system
Generic coding exercises test whether someone can do a generic coding exercise. Use a bounded paid engagement instead — an audit, a prototype, a migration slice, a production hardening task — with real acceptance criteria.
Six steps, in order:
- Define the owned outcome. What must be running, who uses it, what production responsibility the supplier carries.
- Test architecture judgment against a real constraint from your system. Ask for options, risks, a recommended path.
- Inspect delivery mechanics. Planning, code review, QA, release controls, observability, incident response, decision records.
- Interview the actual team — the people doing the work, not sales or leadership.
- Validate security and continuity. Access controls, backups, staffing coverage, escalation. Test the plan with a scenario rather than accepting "we've never had an issue."
- Run the bounded paid engagement.
A pilot that costs money and touches your real code tells you more in two weeks than a reference call tells you ever.
Match the model to the work
Worth saying plainly: an internal hire or a specialist freelancer is often the better call. Stable, narrow, long-lived work belongs in-house. A partner earns its cost when the problem crosses architecture, delivery, operations, and product decisions at once.
Why rate comparison misleads
A lower hourly rate is a real number attached to the wrong question. The savings disappear when designs change repeatedly, questions wait days for answers, or production has no owner. Compare the cost of a stable release and its operation, not one engineering hour.
Time zones work the same way. Overlap between Europe and North America supports a clean handoff and also delays decisions when teams depend on synchronous meetings. Define core overlap hours, asynchronous approval rules, and which incidents justify after-hours escalation — before signing, not after the first missed deadline.
On the market data
For context, since buyers ask: Ukraine's IT Association reported $3.343 billion in computer-services exports for the first half of 2026, up 4.1% year over year, with the US accounting for $1.234 billion or 36.9%. The National Bank reported $6.8 billion in IT-services exports for 2025, 12.6% of total goods and services exports, while the Association's own 2025 figure is $6.6 billion across more than 305,000 tech professionals.
Those numbers don't agree, because the definitions and time windows differ. Check the terms before comparing them, and treat all of it as context rather than as evidence about any vendor. Sector size tells you a market exists. It tells you nothing about whether a specific team has mature operations.
Contract terms worth a lawyer's time
Ukraine's Diia City regime sets rules for qualifying tech companies and includes employment and gig-contract models, under Law No. 1667-IX. A vendor's tax status doesn't change your rights. Confirm whether the supplier is a resident and which entity signs.
Then have counsel cover: IP assignment for code, models, prompts, documentation and designs; data-processing roles, transfers, retention, deletion and incident notice; subcontractor use and approval rights for sensitive systems; security requirements, audit evidence and access removal; sanctions and export controls; and continuity, termination assistance, repository access and knowledge transfer.
That last cluster is the one skipped most often, and it's the one that matters when an engagement ends badly.
For AI work specifically, add: evals, grounding, logging, cost control, human review, and who carries production support.
Keep narrow work narrow. When the work spans AI, legacy systems, data integration, security and production, judge partners by the result they can own — and make them prove it on a paid slice of your real system first.
Full guide — the evidence table, the six-step process, and the engagement models in detail: see the full guide
Written by Bohdan Varshchuk, CTO at Teamvoy. More engineering writing at teamvoy.com/blog.
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