Startup Staffing
KORE1 places developers, engineers, data specialists, and technical leaders into startups from pre-seed through Series C. We move fast because startups don’t have months to wait for a hire. And we understand the difference between someone who thrives inside a 2,000-person company and someone who can actually build something from nothing with five other people in a room.
Most staffing agencies treat startup roles the same as enterprise roles, and what ends up happening is they swap out the company name, adjust the salary band slightly, and send over the exact same batch of candidates they sent to the last three companies that called them. That doesn’t work.
Startups need people who operate without a playbook. Who won’t freeze the first time a requirement changes mid-sprint. Who can handle ambiguity without asking twelve clarifying questions before writing a single line of code. We’ve placed engineers into companies where the entire tech stack changed between the first interview and the start date. That actually happened.
The urgency is real too. A Series A company burning $180K a month can’t afford to leave a critical engineering seat empty for 90 days while a traditional staffing firm runs its standard process. We typically get qualified candidates in front of founders within 7 to 14 days. Not because we cut corners. Because we’ve already built the network.
If you’re scaling an IT team from scratch or adding to an existing one, our broader IT staffing services practice feeds into everything we do here. Same recruiter bench, same speed, different lens.
Roles We Place for Startups
We staff technical roles across the startup stack. Not just software engineers, though that’s obviously the biggest bucket.
- Full-stack and frontend engineers React, Node, Python, Go, whatever the founding team picked and is now stuck with
- Backend and infrastructure The person who sets up your CI/CD pipeline, your monitoring, your cloud architecture, and probably your database schema too, all before you’ve hired a dedicated DevOps team or even decided whether you need one. Our DevOps staffing practice handles those searches when you’re ready for a specialist
- Data engineers and analysts Startups sitting on data they can’t use because nobody has built the pipeline yet. We fill that gap
- AI and ML engineers If you’re building an AI-native product, you need someone who’s shipped models in production, not just trained them in a notebook. Our AI and ML staffing team runs these searches with technical depth that matters at the screening stage
- QA and test engineers The role every startup puts off hiring for until something breaks in production. Don’t be that startup
- Product managers and technical leads Non-coding roles that still require deep technical fluency. We screen for that specifically
- Fractional CTOs and VP Engineering For companies that need senior technical leadership but can’t justify or afford a $350K full-time hire yet. Related reading on the finance side, if you’re weighing whether you also need a fractional CFO for your startup
How We Work With Startups
Discovery call. 20 minutes. We learn what you’re building, who you’ve hired so far, what’s worked and what hasn’t. No pitch deck. No contract pressure.
Sourced candidates within days. We pull from our existing network first. Passive candidates who aren’t on job boards but would move for the right startup opportunity if someone they trust explains what the company is actually building and why it matters, not just forwards them a job description. Active candidates we’ve already screened technically.
Technical screening before you see a resume. Our recruiters can talk through system design, framework tradeoffs, and deployment patterns. We’re not matching keywords against job descriptions. When you get a candidate from us, they’ve already had a real technical conversation.
Flexible placement. Contract if you need to move fast and stay lean. Contract-to-hire if you want to evaluate before committing. Direct hire when you’ve found the right person and want them on your cap table. Same quality of candidate regardless of structure.
Day Average to First Candidates
12-Month Retention Rate
Years in Tech Staffing
Startup Staffing by Funding Stage
| Stage | Team Size | Typical Hires | Best Model |
|---|---|---|---|
| Pre-Seed / Seed | 1–10 | Generalists, full-stack engineers, MVP builders | Contract-to-hire |
| Series A | 10–50 | First dedicated backend, data, DevOps hires | Mix of contract and direct hire |
| Series B–C | 50–200 | Engineering managers, staff engineers, platform teams | Direct hire |
Pre-Seed and Seed. 1 to 10 employees. Hiring generalists who can wear five hats. Full-stack engineers who also do DevOps. A technical co-founder replacement who can build the MVP. Culture fit is everything at this stage because one bad hire doesn’t just slow things down, it poisons the entire team dynamic in a way that takes months to recover from, and at that size you might not survive months. Budget is tight so contract-to-hire works well here.
Series A. 10 to 50 employees. First dedicated hires by function. A real backend engineer. A real data person. Maybe your first DevOps hire. The generalists are still there but you’re adding specialists around them. Speed matters enormously because you just raised money and the board wants to see velocity in two quarters, not four, and every month that engineering seat sits empty is a month your competitors are shipping features you’re still planning.
Series B and C. 50 to 200 employees. Building teams, not filling chairs. Engineering managers. Staff engineers. Platform teams. The conversation shifts from “can this person do the work” to “can this person lead the team that does the work and build the processes, the hiring pipeline, and the engineering culture that makes the next 50 hires productive.” Direct hire is more common here. Retention starts to matter because you’re competing with FAANG offers and the equity upside is less dramatic than it was at seed, which means your compensation story has to be about the role, the product, and the trajectory, not just the options grant.
What Sets Us Apart for Startup Hiring
We aren’t the right fit for every search. But when you need technical talent fast and can’t afford a bad hire, here’s what working with us actually looks like.
Recruiters Who Speak Engineering
Our team screens for real qualifications, not keyword matches. They can talk through system design tradeoffs with your candidates before you ever see a resume.
Built for Startup Speed
Qualified candidates in front of founders within 7 to 14 days. We’ve already built the network. You’re not waiting for us to start sourcing from scratch.
Flexible Engagement Models
Contract, contract-to-hire, or direct placement. We structure the engagement around your funding stage and burn rate, not around our preference.
We Know Startup Culture
Enterprise candidates don’t always translate. We screen for adaptability, comfort with ambiguity, and whether someone has actually built something from scratch before.
Common Questions About Startup Staffing
How fast can a startup staffing agency fill a role?
Depends on the role. A mid-level full-stack engineer with React and Node experience? We usually present 3 to 5 qualified candidates within 7 to 14 days. A staff-level ML engineer with production experience at a startup that’s pre-revenue, someone who’s actually deployed models and not just trained them in a Jupyter notebook? That takes longer, sometimes 3 to 4 weeks, because there are fewer people in that pool and they’re all currently employed somewhere that’s treating them reasonably well. We’ll tell you upfront what the timeline looks like for your specific search rather than making promises we can’t keep.
Is contract or direct hire better for startups?
Neither is universally better. Contract works when you need speed, flexibility, or when runway is tight and you’re genuinely not sure whether the role will still exist in 12 months because the product might pivot or the funding might not come through. Direct hire works when you’ve validated the need and want someone who’s fully invested, equity-eligible, and building alongside the founding team. Contract-to-hire is the middle ground and it’s popular with Series A companies for good reason. You get to evaluate someone in the real environment before making a permanent commitment. More on the structural differences between contract and direct hire staffing models.
What’s the cost of startup staffing services?
Contract roles are billed hourly at a rate that covers the candidate’s compensation plus our margin. Direct hire placements are a one-time fee, typically 20 to 25 percent of first-year base salary, which is standard for the industry and roughly the same as what you’d pay any specialized technical recruiting firm that actually screens candidates properly. We don’t charge upfront retainers for contingent searches. You pay when we make a successful placement. For fractional or part-time technical leadership roles, pricing is structured differently and we’ll walk through the options on the intake call.
Do you work with pre-revenue startups?
Absolutely. A fair number of our startup placements are with companies that haven’t generated revenue yet and won’t for another year or two. Pre-seed and seed stage. What matters to us is whether you can actually hire, meaning you have funding committed or enough runway to pay the person. We’ve turned down engagements where the founder wanted to hire but didn’t have the capital secured. That’s bad for the candidate, bad for the founder, and bad for us.
How do you screen technical candidates for startup roles?
Differently than for enterprise roles. Enterprise screening checks whether someone can do the defined job. Startup screening checks whether someone can do a job that hasn’t been fully defined yet and will change in three months. We assess adaptability, breadth of experience, comfort with ambiguity, and whether they’ve built something from scratch before versus only maintained existing systems. Our recruiters run real technical conversations, not checkbox assessments. We ask about architectural decisions, tradeoff reasoning, and what happened when something broke. The AI and ML staffing team runs an even deeper technical screen for machine learning roles.
What industries do your startup candidates come from?
All over. SaaS, fintech, healthtech, edtech, e-commerce, developer tools, cybersecurity, and climate tech. Industry background matters less in startup hiring than it does in enterprise, mostly because startups move so fast that domain expertise from a previous industry becomes stale within six months anyway and what actually matters is the ability to learn on the fly. A senior backend engineer who built a payments system at a fintech startup can absolutely transition to a healthtech company. What matters more is the operating environment. Have they worked at a company with fewer than 50 people? Have they shipped without a QA team? Have they operated under real resource constraints? That’s what we screen for.
Can you help build an entire engineering team from scratch?
We’ve done it more than a few times, and the logistics are honestly the hardest part. Usually for Series A companies that raised a round and need to go from 2 engineers to 10 within a quarter. The process is different from filling a single role. We work with the CTO or VP Engineering to define the team structure, figure out which roles to fill first and which can wait a quarter, stagger start dates so onboarding doesn’t collapse under its own weight, and build in redundancy for the roles that are hardest to fill because you’ll lose candidates to competing offers along the way. It’s more like workforce planning than staffing at that point. If you’re also hiring outside of engineering, our broader IT staffing services team can run those searches in parallel.
Ready to Staff Your Startup?
Start with a 20-minute intake call. We’ll ask about what you’re building, what stage you’re at, and what’s gone wrong with hiring before so we don’t repeat it. No commitment. Just a conversation to see if we’re the right fit.