Whether you are launching a product, scaling infrastructure, or shipping features faster, HireCade helps you hire high-performing software developers who are pre-vetted using our proprietary AI Interviewer for coding skills, problem-solving, and communication.
Define the first project rather than a list of technologies, decide whether the work needs employment or a contract, then screen with a structured technical interview every candidate takes. Run one live exercise resembling the real job, check debugging and code review judgement, verify work history, and agree the time zone overlap in hours before you make the offer.
That sequence works because it front-loads the part teams usually leave until last. Most engineering searches begin with a stack keyword list, produce a pile of resumes that all match it, and then burn senior engineering hours filtering. Deciding what the person will own in their first ninety days does more to narrow the field than any keyword filter.
The screening step is where comparability comes from. Ad hoc phone screens produce impressions that cannot be ranked against each other, because every candidate was asked different questions by a different person on a different day. A structured interview with follow-ups on the candidate's own answers gives you a shortlist you can actually order.
Everything after that is your judgement, not ours. Your engineers should still run a final loop covering architecture taste, how someone handles ambiguity, and whether they will work well in your codebase. Our part is making sure that loop is spent on plausible hires rather than on filtering.
A typical engineering req burns roughly 13 hours on sourcing and another 20 on resume screening before anyone technical talks to a candidate. Most of that time is spent rejecting people. By the time a strong candidate reaches your team, they have usually accepted another offer.
We move the screening to the front. Every developer in our pool has completed a structured technical interview with our AI Interviewer before you ever see their profile, so the shortlist you receive is people who have already demonstrated they can write, reason about, and debug real code.
That changes what your engineers spend interview time on. Instead of filtering, they are assessing fit: architecture judgement, how someone handles ambiguity, and whether they will thrive in your codebase.
Matched only with proven, production-ready engineers tested on real-world skills rather than keyword-matched resumes.
APIs, databases, and interfaces. Our developers specialize across the whole stack.
Hire in days. Full-time, part-time, or per-project, with no minimum commitment.
Work with developers in your preferred hours, wherever your team happens to sit.
React, Next.js, Angular, and Vue, including design system and accessibility work.
Node.js, Python, Java, Go, and Rust, with API and data modelling depth.
Owns a feature end to end, from schema through interface.
AWS, Azure, and GCP, plus Terraform, Kubernetes, and CI/CD pipelines.
Native iOS and Android alongside Flutter and React Native.
Pipelines, warehousing, feature stores, and model deployment.
Test strategy, Playwright and Cypress suites, and release gating.
Senior technical direction without a full-time executive hire.
Application security reviews, threat modelling, and compliance readiness.
Internal tooling, build times, developer experience, and deployment safety.
Delivery, review culture, and hiring for a team you already have.
Customer-facing implementation work, APIs, and third-party integrations.
Greenfield builds and feature delivery.
Service boundaries, contracts, and versioning.
Query tuning, sharding, replicas, and migrations.
Build pipelines, IaC, observability, and cost control.
Raising standards on an existing codebase.
Incremental migration off frameworks that are holding you back.
Finding where latency and cloud spend actually come from.
Suites that catch regressions instead of flaking.
Payments, identity, messaging, and data providers wired in properly.
Every candidate completes a structured technical interview with our AI Interviewer before entering the pool. It is the same interview for everyone applying to a given role, which makes the results comparable in a way that ad hoc phone screens never are.
The interview is conversational and adaptive. Candidates explain their reasoning out loud, get asked follow-up questions on their actual answers, and work through debugging scenarios rather than recalling trivia. We score and record the session, so you can review how someone thinks before you commit an hour to them.
We also run cheating detection on every session. That matters more than it used to, and it is the main reason our shortlists hold up in your own technical loop.
What we deliberately do not do is score candidates on rapport or on how closely their background resembles your existing team. Both feel like signal in an unstructured interview and neither predicts whether someone can do the job.
What the screen actually checks
We source, screen, and shortlist against your req. Contingency pricing means you pay on placement.
Add capacity for a quarter or a project, priced as a percentage of the engagement.
A tech lead or CTO for one or two days a week while you are still finding product-market fit.
Run the whole process yourself, adding AI screening per resume or per interview as needed.
Employer of Record or Contractor of Record where you have no legal entity in the person's country.
Start scoped and time-bound, then convert if the working relationship proves itself.
Tell us about your product, stack, and engineering goals.
Screened for hands-on ability, not just resumes, with interview recordings attached.
Run your own final loop and get someone into sprint planning the same week.
Ramp teams up or down with no long-term hiring risk.
All four can end with a working engineer on your team. They differ in who does the screening, how much of your own time the search consumes, and what you are exposed to if the hire is wrong.
| Factor | HireCade | Staffing agency | Freelance marketplace | In-house hiring |
|---|---|---|---|---|
| Who screens technically | Structured AI interview before shortlisting, with a recording you can review | Usually a recruiter without a technical background | Nobody: ratings and reviews stand in for screening | Your own engineers, using interview time you would rather spend shipping |
| Your time before the first good candidate | Review a shortlist and run your final loop | Review submissions, many of which are keyword matches | Read profiles and proposals, then test candidates yourself | Sourcing plus resume screening, which is where most of the hours go |
| Comparability of candidates | Same interview for every candidate on a role, so scores rank | Varies by recruiter and by day | Not comparable: different clients, different work, different standards | Comparable only if you run a structured loop yourself |
| Cost structure | 10% refundable retainer credited toward a 20% placement fee, or 30% of contract engagement fees | Typically a percentage of salary, often with less transparency on screening | Platform fee plus an hourly or fixed rate | No external fee, but real internal cost in engineering and recruiting hours |
| Best suited to | Roles where technical screening is the bottleneck | High-volume or contract staffing where you accept doing the technical filtering | Small, well-specified, short pieces of work | Teams with recruiting capacity and engineers with interview time to spare |
| Global employment handled | Employer of Record or Contractor of Record available with the placement | Sometimes, depending on the agency | No: you carry the classification question yourself | Only if you already have an entity or a provider |
If your constraint is recruiting capacity rather than screening, the free applicant tracking system with AI resume ranking and interview screening may be the cheaper answer. We will say so.
Writing new code is a smaller part of the job than job descriptions imply. A working week is mostly reading existing code, clarifying a requirement that was ambiguous, reviewing someone else's pull request, adjusting a test that broke for an unrelated reason, and shipping a change behind a flag. The developers who feel fast are usually the ones who spend the most time on those surrounding activities, because they avoid rework.
The shape changes with the team. At a startup with three engineers, one person owns a feature from schema through interface, talks to customers, and gets paged when it breaks. In a larger organisation the same person might own one service, coordinate with two adjacent teams, and spend real time on migration work nobody outside engineering will ever notice.
Understanding which version of the job you are hiring for matters more than the stack. Someone who has thrived with tight scope and strong platform support can struggle when there is no staging environment and no on-call rotation, and someone used to owning everything can be frustrated by a process-heavy team. Describe the reality in the brief and you filter for fit before the first call.
Strong engineers ask questions before they write code. Given a vague ticket, they establish what the change is meant to achieve, what is already true in the system, and what should happen in the failure case. Weaker candidates start typing immediately, which looks decisive in an interview and creates most of the rework in a real codebase.
The second signal is how someone handles an unfamiliar fault. Good debuggers form a hypothesis, pick the cheapest test that would disprove it, and narrow the search space deliberately. Candidates who change several things at once, or who explain a bug by blaming a library without evidence, will do the same under real incident pressure.
Code review behaviour is the most underrated signal of all. Ask a candidate what they look for in someone else's pull request. People who mention naming and formatting are describing a linter. People who mention missing error handling, unclear ownership of state, tests that would pass even if the feature were broken, and whether the change is reversible are describing judgement you cannot install later.
Most engineering job descriptions fail in the same way: a long list of technologies, no description of the work. Strong candidates read a list of fifteen tools as a sign that nobody has decided what the role is, and they self-select out. The brief that gets replies describes the first project, the problem it solves, and who the person will work with.
Separate the requirements you genuinely cannot train from the ones you can. Deep experience with your primary language is usually real. Familiarity with your specific cloud provider, monitoring vendor, or queue is usually learnable in a fortnight by anyone who has used a comparable system. Every non-negotiable you add shrinks the pool, so spend them deliberately.
Be explicit about the constraints candidates will otherwise ask about on the first call: time zone overlap, whether the role is employment or contract, how decisions get made, and what the codebase is actually like. If there is significant legacy work, say so. Candidates who are fine with legacy work exist, and the ones who are not will cost you a full interview loop to discover.
Design the loop around the work the person will actually do. If the role is feature delivery in an existing codebase, the highest-signal exercise is a small change in a realistic repository with tests, not an algorithm puzzle on a whiteboard. If the role is greenfield architecture, then a design discussion is the right exercise and a coding puzzle is mostly noise.
Use the candidate's own history as the backbone of the interview. Pick one project they list, then go deep: what the constraints were, which decision they now regret, what they measured, and what they would do differently. Fabricated experience collapses at the third follow-up question, and genuine experience gets more interesting.
Keep the exercise identical across candidates and agree the scoring dimensions before you start. Interviews that drift into rapport produce hires who resemble the interviewer. Our AI Interviewer exists for the same reason: every candidate for a given role gets the same structured interview with follow-ups on their actual answers, and you get the recording and score before you spend your engineers' time.
Titles are inconsistent between companies, so define levels by the amount of ambiguity someone can absorb. A junior engineer delivers a well-specified task with review. A mid-level engineer delivers a feature, breaks it into steps themselves, and knows when to ask. A senior engineer takes a business problem with no agreed solution, chooses an approach, and is accountable for the consequences of that choice.
Above that, staff and principal engineers are mostly leverage rather than throughput. Their value is in decisions that stop whole categories of future work, in making other engineers faster, and in owning the parts of the system nobody wants to touch. Hiring at that level to close a sprint backlog is an expensive mistake, and strong candidates will notice from the brief and pass.
A fractional tech lead or CTO is worth considering when you need senior judgement but not senior throughput. One or two days a week is often enough to set architecture, establish a review culture, and unblock a small team, and it is a far cheaper way to find out what your permanent first engineering hire should look like. If you would rather have an outside team build the first version, our product build service covers that path.
There are four sensible ways to engage, and picking the wrong one is more expensive than picking the wrong candidate. A full-time hire suits work that needs accumulated context. Contract and staff augmentation suit a scoped push, such as a migration or a release. A fractional lead suits judgement without throughput. Running the search yourself on our free applicant tracking system suits teams with recruiting capacity who mainly want screening help.
Our pricing follows that split. Full-time placements are contingency-based: a 10% retainer against estimated first-year base salary, refundable if no hire is made, credited toward a 20% placement fee when someone starts. Contract placements are 30% of engagement fees. Self-serve is free for the applicant tracking system, with AI resume ranking at $0.10 per resume and AI interview screening at $5 per interview. Developer salary levels vary enormously by market and specialism, so use our salary and level guides to set a range rather than assuming one.
The practicalities decide whether a good hire works out. Agree the overlap window in hours and put it in the offer. Decide before day one who reviews the code, where decisions get recorded, and what the on-call expectation is. If the person sits in a country where you have no entity, Employer of Record or Contractor of Record gives you a compliant structure instead of an invoice and a risk you have not priced.
For common stacks such as React, Node, Python, and Java, we usually return a reviewable shortlist within three to five business days, because those candidates are already screened and in the pool.
Narrower asks take longer. A Rust engineer with payments domain experience, or someone who needs to be onsite in a specific city, can take two to three weeks. We tell you which category your role falls into before you commit.
Full-time placements are contingency-based: a 10% retainer with a 20% placement fee against first-year base salary, so the bulk is only owed once someone actually starts.
Contract placements are billed at 30% of the engagement fees. If you would rather run the process yourself, the applicant tracking system is free, and you can add AI resume ranking at $0.10 per resume or AI interview screening at $5 per interview.
A coding test tells you whether someone produced a passing solution. It does not tell you how they got there, and it is trivially outsourced or automated.
Our interview is a conversation. It asks follow-up questions based on what the candidate actually said, watches them debug something unfamiliar, and runs cheating detection throughout. You get a recording and a score, so your engineers can judge reasoning rather than just output.
Yes, and we expect you to. Our screening exists to make your final loop worth running, not to replace it.
Teams typically go from interviewing eight candidates to find one hire, down to two or three, because the obvious no-hires never reach them.
Use a live exercise for the decision and a take-home only when the work genuinely cannot be observed in an hour. A live session shows you how someone reasons, asks questions, and reacts to a changed requirement, which is the part a finished artefact hides.
If you do send a take-home, keep it under a couple of hours, pay for anything longer, and always follow it with a live review where the candidate extends their own code. That review is the real signal: it is very hard to discuss code you did not write.
Ask about a system the candidate has operated rather than a famous product they have only read about. Have them sketch it, then ask what broke, what they would change, and which part they would refuse to build again.
Good answers name constraints before components: expected traffic shape, consistency requirements, failure behaviour, and cost. Candidates who jump straight to a diagram of boxes without asking a single clarifying question usually do the same thing in your codebase.
Match the level to how much ambiguity the work carries, not to the size of the codebase. Junior and mid engineers are effective when the problem is already framed and someone reviews their work. Senior engineers are worth it when the requirements are unclear and the wrong architecture would be expensive to undo.
Most early teams over-hire on title and under-hire on ownership. If nobody on staff can review the work, you need a senior hire first even if the tasks themselves look routine.
Frontend work in React, Next.js, Angular, and Vue, backend in Node.js, Python, Java, Go, and Rust, mobile in native iOS and Android as well as Flutter and React Native, plus DevOps, data engineering, machine learning, QA automation, and application security.
If your stack is unusual, tell us before the search starts. We would rather say a niche combination will take longer to staff than send you adjacent profiles and let you discover the gap in a technical loop.
Contract suits scoped, time-bound work where you mainly need throughput: a migration, an integration, or extra capacity for a release. Employment suits work that requires accumulated context, code ownership, and being on call for decisions months later.
The distinction is legal as well as practical. Classification depends on control, integration, and duration rather than on what the agreement is titled, so if you intend to direct someone's daily work indefinitely, treat that as employment. Our Employer of Record and Contractor of Record services exist so you can pick the right structure rather than the convenient one.
Yes. If you want someone in a country where you have no legal entity, our Employer of Record service employs them on your behalf at $499 per employee per month.
For contractors, Contractor of Record handles the engagement so you are not carrying misclassification risk. Both can be arranged as part of the same placement.
We filter on committed overlap hours rather than on country, because the two are not the same thing. You tell us the window where the person must be reachable, and candidates confirm they can work it sustainably.
Four overlapping hours is enough for most product teams: it covers standup, review, and one deep discussion. Fewer than that works only when the work is well specified and handoffs are written down properly.
Tell us early. For contract engagements we replace the person and you are not billed twice for the same seat.
For full-time placements, the replacement terms are set out in the placement agreement before you sign, and we would rather rework a search than argue about a fee.
Related products and guides for engineering hiring: the screening tools that sit under this service, the employment structures that make a global hire compliant, and the salary and level data you need before writing an offer.
Every hiring, screening, and employment product in one place.
Sourcing, resume ranking, and AI screening priced per resume and per interview.
Unlimited jobs, candidates, and team seats if you want to run the search yourself.
Hand the technical loop to vetted interviewers when your engineers have no time.
A weekly shortlist of pre-screened engineers before you open a formal req.
When the honest answer is an outside team rather than a first hire.
Retainer, placement fee, contract, and self-serve rates side by side.
Employ an engineer in a country where you have no legal entity.
Engage contractors compliantly instead of carrying classification risk.
Visa and sponsorship support when the engineer needs to relocate.
O-1A, H-1B, EB-1, and EB-2 NIW petition help for the people you hire.
Larger delivery teams rather than individual engineering hires.
Set a range from market data rather than from the last offer you made.
Compare compensation across roles, companies, and locations.
Map a candidate's previous level onto your own scope expectations.
Grade codes and promotion timelines at large service firms.
Real questions by company and role, useful for designing your own loop.
Discussions on hiring, tooling, and technical practice.
Longer written guides on screening, interviewing, and offers.
Join teams moving faster with elite developers pre-vetted by HireCade.
