How We Evaluate Candidates

We hire for the traits that make someone thrive in fast-moving, high-stakes deployments. Every candidate is evaluated on four things:

• Responsibility & dedication. You take full ownership of your work and follow through. When a deployment is on the line, you do whatever it takes to get it right — and you can be counted on.
• Speed of learning. Our stack, our hardware, and our customers change fast. You pick up new tools, technologies, and contexts quickly and turn them into results without hand-holding.
• Multi-tasking capability. You juggle code, hardware, customers, and live events at once — often in the same day — and keep all of them moving without dropping the ball.
• Communication skills. You explain technical concepts clearly to anyone — a mayor, a CEO, a teammate, or a curious bystander — and you keep the team aligned under pressure.
• Who You Are
• Ideally, you've delivered enterprise software at a startup, or run enterprise projects at a consulting firm — you know how to ship for demanding customers and manage delivery end to end.
• You code. Python, JavaScript/TypeScript, or both. You've built and shipped things that went beyond the spec.
• You're genuinely excited about AI — not just the hype, but how LLMs, computer vision, and multimodal models actually work under the hood.
• Hardware doesn't scare you (or it does, but you want to learn anyway). You're willing to carry a monitor, run cables, and troubleshoot on-site.
• You communicate clearly — to a mayor, a CEO, or a curious bystander at a trade show.
• You thrive in chaos. Startups are messy. Deployments have surprises. You stay calm, figure it out, and keep going.
• You're a team player who brings energy, not ego.

Bonus Points

• Experience with LLM frameworks (LangChain, LlamaIndex), prompt engineering, or RAG pipelines.
• Familiarity with edge computing, IoT, AV systems, or robotics.
• Prior startup or hackathon experience where you shipped something under pressure.
• Background in CS, EE, information systems, or a related technical field.

Why You'll Love This

• World-stage experiences. Your LinkedIn won't say "updated Jira tickets." It'll say "deployed AI at the Super Bowl."
• Full-stack, full-real. AI + software + hardware + customer-facing — you'll build a skill set most engineers don't reach until years into their careers.
• Silicon Valley, front row. You'll work at the center of the physical AI movement, with the connections and momentum that come with it.
• Mentorship that matters. You'll work directly with founders and senior engineers who want to see you grow — not hand you busywork.
• Real ownership & growth. Top performers take on more scope fast — leading deployments, owning customers, and shaping the product.
• Competitive salary, equity, and benefits.