HR as a Service
Building a core team and scaling hiring for a fintech client under non-standard constraints
Read MoreContext
A fintech client approached us with multiple parallel initiatives and an urgent need to fill three roles (one role with two openings, and two additional roles with one opening each). The ecosystem already included investors and a CTO, but there was no established core team, which made hiring requirements unusually specific.
The engagement model required two parallel hiring tracks:
- hiring direct contractors to form the client's core team, and
- later scaling with Polytech hires who would integrate into the client's organization.
Key Constraints
- 1
Direct-contract candidates
the client did not accept Polytech technical interviews for this track (our tech interview applied only to Polytech hires). - 2
Assessment approach
the client used a large take-home assignment (4+ hours), increasing candidate drop-off risk. - 3
Sourcing limitations
the client was not willing to pay third-party platform fees (e.g., paid sourcing services). - 4
Location
not critical for the client (enabled broader EU/UA reach).
Challenge (Why It Was Hard)
We had to maintain hiring quality and speed while:
- running a direct-contract track without our technical interview gate
- reducing drop-off from a time-consuming take-home task
- operating with free sourcing channels only
- keeping candidates engaged while investors/CTO were involved in decision-making and scheduling
Our Approach
We redesigned the hiring process to behave like a conversion funnel: reduce unnecessary candidate effort, increase clarity, add fast filters, and enforce tight SLAs on feedback. The goal was simple: keep the bar high while eliminating friction.
What We Implemented
Process adaptation to client constraints
- Reworked the take-home assignment with our experts: removed "commodity" checks (e.g., dockerization rituals, generic Git routines, "fully production-ready solution" expectations that can be validated via interview). Result: less wasted candidate time and clearer evaluation criteria.
- Focused on free sourcing: LinkedIn as the primary channel plus free job boards in Ukraine and Europe.
- Expanded initial screening: added a short technical block tailored to the client's specific projects to filter mismatches early without slowing the funnel.
Additional steps introduced to increase conversion and quality
- Candidate Brief (1-pager): a concise document describing the project, role, technical context, and expectations — improving conversion into the assessment stage.
- Modular assessment options: allowed the take-home to be completed in parts; alternatively offered a 90-minute live session instead of the full take-home to preserve quality with less candidate burden.
- Feedback SLAs: 48 hours for stage feedback; 72 hours for a next-step decision.
- Early sell call with CTO/investor: improved engagement and acceptance among strong candidates.
- Asynchronous mini-quiz (12–15 minutes): used before repeat technical interviews with the client — a lightweight filter to avoid forcing another "4+ hour" take-home.
Execution & Funnel Metrics
- First two openings (same role, 2 seats): filled within 2 weeks of search.
- Due to the absence of our technical interview for direct-contract candidates, we ran a more extensive sourcing effort:
- 36 qualified candidates in the pipeline → 9 completed the assessment → 2 offers → core team formed.
- More complex role (Senior Python AI Engineer): closed in an additional 3 weeks from 13 candidates.
- QA Engineer: filled in 2 days thanks to an existing pool of available specialists.
Results / Client Outcome
- The client formed its initial core team quickly while keeping quality control and decision-making transparent despite a non-standard hiring setup.
- Candidate drop-off was reduced by removing low-signal effort and introducing fast filters and alternative assessment formats.
- The model proved repeatable for the next scaling phase where Polytech hires integrate into the client's organization.