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recogni case study

The reality in today’s automotive tech landscape is clear: companies developing AI solutions for electric and self-driving vehicles need specialized engineering talent that simply doesn’t exist in sufficient numbers within driving distance of Silicon Valley headquarters.

Recogni, a California-based startup developing cutting-edge AI hardware for autonomous vehicles, faced exactly this challenge in 2019. With 28 engineers split between California and Munich working on complex hardware-software integration projects, their CTO Eugene Feinberg knew traditional local hiring wouldn’t scale fast enough to meet their ambitious product roadmap.

What we’re seeing with automotive hardware startups is a fundamental shift—the most critical engineering talent for vehicle AI systems isn’t clustered in traditional tech hubs. Instead, it’s distributed globally among engineers who understand both embedded systems and automotive-grade reliability requirements.

Strategic Remote Team Formation in Serbia

Given the current market shift toward distributed automotive engineering teams, Recogni needed partners who understood both the technical complexity of their hardware-software stack and the unique challenges of automotive product development timelines.

Here’s what most companies miss about automotive engineering hiring: You’re not just looking for React developers or GPU programmers. You need engineers who can work across the full stack—from low-level hardware optimization to real-time software systems—while maintaining the safety-critical mindset that automotive applications demand.

Our approach focused on three critical areas that traditional recruitment processes overlook:

Technical Depth in Automotive-Specific Skills

Instead of generic “C++ developer” requirements, we identified candidates with experience in:

  • GPU programming for real-time AI inference (not general graphics programming)
  • React development for automotive UI systems (understanding safety-critical interface requirements)
  • Hardware-software integration for embedded automotive systems

Autonomous Decision-Making Capabilities

Let’s rethink how you approach remote automotive engineering. These aren’t typical software engineers who need constant direction. Automotive hardware development requires engineers who can troubleshoot complex integration issues independently, make critical decisions about system architecture, and communicate technical challenges across hardware and software domains.

Cross-Functional Integration Skills

The modern automotive tech stack requires engineers who can bridge multiple disciplines. Our candidates needed to collaborate effectively with hardware engineers in Munich while developing software that would eventually run on custom silicon—requiring both technical depth and exceptional async communication skills.

The Results: 100% Success Rate and $83,192 Savings Per Position

The numbers tell the story:

  • 3 engineers hired with 100% success rate in placement
  • 1 month from initial screening to signed contracts
  • $83,192 average savings per position compared to Silicon Valley hiring
  • Immediate productivity with no extended onboarding period

But the real impact goes beyond cost savings. Within months of building their Belgrade team, Recogni secured $25 million in Series A funding led by GreatPoint Ventures, with participation from Toyota AI Ventures and BMW i Ventures.

Why This Approach Works for Automotive Hardware Startups

Based on our experience with similar roles, automotive companies that successfully scale their engineering teams share three characteristics:

  1. They recognize that automotive AI development is fundamentally different from general software development—requiring engineers who understand real-time constraints, safety requirements, and hardware limitations.
  2. They prioritize engineering autonomy over management overhead—remote automotive engineers need to solve complex problems independently, especially when working across hardware-software boundaries.
  3. They focus on cultural fit and communication skills alongside technical expertise—automotive development cycles require precise coordination between distributed teams working on interdependent systems.

Focus on Innovation While We Handle Talent Acquisition

While Recogni’s engineering team was solving complex AI inference optimization problems, our recruitment process was running in parallel—identifying and vetting candidates who could contribute immediately to their hardware-software integration challenges.

The automotive tech talent shortage means companies can’t afford to take months refining job descriptions and conducting endless interview rounds. Recogni needed engineers who could start contributing to their autonomous vehicle AI platform within weeks, not quarters.

Our process eliminated the typical automotive engineering hiring bottlenecks:

  • No resume screening cycles that miss candidates with unconventional but relevant experience
  • Technical assessment focused on actual automotive challenges rather than generic coding tests
  • Cultural evaluation specific to remote automotive development rather than general team fit

What This Means for Your Automotive Engineering Team

If you’re developing AI systems for vehicles, autonomous driving technology, or automotive-grade hardware, the traditional approach of posting jobs and hoping qualified candidates apply isn’t working in today’s market.

The evolution toward remote-first automotive engineering teams isn’t just about cost savings—it’s about accessing the specialized talent needed to compete in the autonomous vehicle space. Engineers with both embedded systems expertise and automotive safety mindset are globally distributed, not concentrated in any single tech hub.

Let’s discuss how this applies to your specific automotive engineering challenges. Whether you’re building AI inference hardware, developing safety-critical vehicle software, or integrating complex automotive sensor systems, the right remote engineering talent can accelerate your development timeline while maintaining the quality standards your automotive applications require.

Ready to Build Your Remote Automotive Engineering Team?

The automotive industry is moving toward software-defined vehicles, AI-powered safety systems, and autonomous driving capabilities. Your engineering team needs to evolve just as quickly.

Schedule a consultation to discuss how we can help you identify and hire the specialized automotive engineers your product roadmap demands—without the geographic limitations that slow down traditional hiring processes.

Contact us to learn more about building high-performance remote teams for automotive hardware development.

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Very attentive, resourceful and helpful for first-time companies who would like to hire contractors or employees remotely. The quality of people is very good.
Eugene Feinberg, CTO Recogni

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