Where to find a founding engineer for AI startups?
Dover
September 12, 2025
•
4 mins
A founding engineer is your technical co-founder without the formal title. They're the first engineering hire who takes ownership of building your product from the ground up, implementing features and creating the foundation.
In AI startups, founding engineers wear multiple hats as they help:
Architect your initial tech stack
Contribute to product strategy based on what's technically feasible
Founding engineers often help with technical hiring as you scale, represent your company at conferences, and help with bridging your vision and technical reality.
For AI startups, this role is even more important because the tech scene changes every minute. Your founding engineer needs to stay updated with the latest developments in AI engineering, while building production-ready systems that can scale.
The best founding engineers combine deep technical skills with entrepreneurial instincts. They can build fast when speed matters and architect for scale when growth demands it.
AI startups are constantly working with challenges like rapidly evolving tech, managing complex model deployments, and often dealing with major computational costs from day one.
They make choices that have massive implications for your burn rate and technical debt. A founding engineer can help you:
Avoid costly architectural mistakes: They should understand the tradeoffs between different AI approaches and decide whether to build custom models, fine-tune existing ones, or use APIs.
Achieve product-market fit: They can quickly prototype new features, experiment with different model approaches, and help you iterate based on user feedback
Fundraise: VCs want to see that you have someone who can handle the complexities of AI development and scale your technology as you grow.
The talent market for AI engineers is incredibly competitive right now. Companies like OpenAI, Anthropic, and Google are paying top dollar for experienced AI talent. Having a founding engineer who's invested in your success through equity gives you a major advantage in building your initial team.
Technical expertise is obviously important, but the specific skills matter. Look for candidates with:
Hands-on experience building various production AI systems
Experience with the full stack over deep specialization
Understanding to articulate technical tradeoffs and it's impact
Cultural fit and adaptability to startup environment
Most importantly, find someone who's ready to trade stability for the opportunity to build something from scratch.
Technical Skills | Soft Skills | Experience Markers |
|---|---|---|
LLM fine-tuning and deployment | Comfort with ambiguity | Previous startup experience |
Python/PyTorch or TensorFlow | Strong communication | Built 0-to-1 products |
Cloud infrastructure (AWS/GCP) | Leadership potential | Shipped production AI systems |
API design and scaling | Bias toward action | Technical decision-making |
Hire a Founding Engineer In-House vs Hire Through Dover
Most early-stage AI startups have a choice: try to recruit founding engineers themselves or work with specialized recruiters who understand the space. Both approaches have merits, but the decision often comes down to time, expertise, and cost.
The challenge in today's market is that you're competing against well-funded companies with dedicated recruiting teams and employer brands that attract top talent.
Without existing relationships, you might struggle to reach the best candidates.
Working with fractional recruiters through Dover gives you access to specialized expertise without the overhead of hiring full-time recruiting staff. Our recruiters understand the AI talent market and have existing relationships with engineers interested in founding roles.
The cost comparison often favors fractional recruiting for early-stage companies. A full-time technical recruiter costs an average of $150k+ annually, while you pay fractional recruiting only for the hours you need them.
You get experienced recruiters who specialize in startup hiring without the long-term commitment.
Dover's approach is particularly valuable for AI startups because our fractional recruiters understand the technical requirements and can effectively screen candidates before they reach you. This saves you time and you're only interviewing candidates who meet your technical bar.
How to source founding engineers with Dover
Working with Dover starts with clearly defining your founding engineer requirements. Our recruiters will help you create a detailed profile that covers technical skills, experience level, and cultural fit criteria. This upfront work makes sure we're targeting the right candidates from the start.
Dover's recruiters use multiple sourcing channels to find AI engineering talent by:
Tapping into our existing network of engineers
Actively sourcing from companies with strong AI teams
Referrals from our portfolio of successful placements
The process typically begins with a strategy session where we discuss your specific needs, timeline, and budget constraints. Our recruiters will share insights about the current market and help you position your opportunity.
Once we start sourcing, you'll receive regular updates on candidate pipeline and market feedback.
Our recruiters handle initial screening calls to check technical background before scheduling interviews with your team. This way, you only interview qualified candidates.
We also provide guidance on interview processes and help you create technical assessments that effectively test founding engineer candidates. Our experience with AI startups helps us understand what works for screening technical talent in this space.
How to assess and screen candidates
Looking at founding engineer candidates requires a different approach than hiring for existing engineering teams. You need to assess both technical competency and their ability to thrive in fast-moving environment. During assessment, focus on:
Technical screening test with AI/ML: Ask them to walk through a complex system they've built and explain the technical decisions they made.
Architectural thinking: Pay attention to how they communicate technical concepts and whether they consider business constraints in their technical choices.
Cultural fit: They need to be comfortable making decisions and adapt to evolving needs. Ask about times they've had to pivot technical approaches or work with limited resources.
Reference checks: Speak with previous managers and colleagues about their technical leadership, and how they handle pressure.
Involving technical advisors or investors: They help you get additional perspective on candidates' technical depth and avoid blind spots in your evaluation.
Bonus Tip: For the technical interview, consider giving candidates a realistic problem similar to what they'd face in your startup. Skip abstract coding challenges, and present them with a scenario like "design a system to fine-tune and deploy a custom LLM for our use case."
This reveals their practical experience and problem-solving approach.
How to structure compensation for founding engineers
How to close and onboard founding engineers
Frequently Asked Questions
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