Backend and platforms
Domain-heavy services, APIs, integrations, data models, and infrastructure that remain operable after release.
HILLS Lab
HILLS Lab is a founder-led engineering studio in Split. We build and improve backend systems, product workflows, and operational infrastructure for teams that need ownership, speed, and dependable delivery.
Focus
Backend and platform engineering for domain-heavy products
Integrations, data, performance, and operational reliability
Product delivery from ambiguous problem to production
AI-assisted workflows with clear sources, permissions, and review boundaries
Use cases
Domain-heavy services, APIs, integrations, data models, and infrastructure that remain operable after release.
From an ambiguous problem and explicit trade-offs through implementation, testing, release, and real user feedback.
Faster engineering workflows with clear repository context, scoped access, review boundaries, and explicit production actions.
Deploys, observability, incidents, runbooks, migrations, and fallback paths that keep systems legible under pressure.
Recommendations
Povio, ReneVerse, and Tilt are HILLS Lab work. The other recommendations show the wider engineering track record behind HILLS Lab.
Open, professional, transparent in communication, and reliable on every agreed scope.
A top-tier engineer who made next-level impact across core Web2/Web3 services and real-time ad targeting infrastructure.
Multiple people have called out the quality and speed of Hrvoje's work across several projects.
Wider engineering track record
Curious, proactive, and willing to take responsibility beyond his role early in his career.
Someone we could truly rely on, not afraid to take responsibility and push new initiatives forward.
An exceptionally capable engineer whose code was built to last in a highly challenging hypercar telemetry and OTA domain.
Thesis
The highest-value part of senior engineering is not the amount of code produced. It is finding the real constraint, explaining the trade-off clearly, and delivering a system the team can safely continue to evolve.
Engagement model
One conversation and a short review of the product, domain, team, existing system, and the outcome that matters.
We map the domain, existing system, ownership, risks, and the real constraint behind one concrete workflow.
We build the smallest serious part of the solution that can be tested with real data, users, and operational conditions.
You get a verified change, documented decisions, and a clear next step for handoff, continued implementation, or ongoing support.
Six checks before the change
The same questions apply to code, a migration, an AI workflow, or a production operation. Speed only matters when the change stays understandable and verifiable.
Which repo, ticket, incident, document, or decision supports the claim.
Whether the information is still current or a newer record has replaced it.
Whether this context is allowed for this team, tool, actor, and task.
What could break production, leak data, or lead the agent to a wrong conclusion.
What changed since the last run, deploy, incident, or recorded decision.
Whether a person can replay the path: sources, permissions, decision, and result.
PLAYGRND proof point
We build PLAYGRND as a public record for amateur football: SSR web, a private Go API, Postgres/Redis, WhatsApp magic links, claim/correction loops, admin review, and recomputable season aggregates. It shows how HILLS works when product, architecture, data, release, and operations share one owner.
For local software teams
Local companies often do not need another vendor or generic demo. They need a senior engineer who can understand the domain quickly, work with the existing team, and own a concrete outcome.
Notes
Short notes on backend decisions, product workflows, operations, and the safe use of modern AI tooling in real software work.