We unlock ground truth for the enterprises that power the global economy.

There are billions of important conversations taking place in real time each day in hospitality, food service, retail, logistics and countless other industries - conversations with employees and conversations with customers. Until today, those conversations vanished into thin air the second they happened.

Arbor turns in-person conversations into executive-grade strategic intelligence. We're closing enterprise contracts at companies in some of the most vital industries of the world. This problem is huge and there’s nothing quite out there to solve it. Come join us if you're a product builder who gets this space!

The Role

This is a foundational engineering hire. You'll report directly to our CTO and co-founder, and work shoulder-to-shoulder with him on the core product. Umi, our AI researcher, runs natural voice interviews with frontline employees and customers at scale, then turns thousands of conversations into intelligence leaders act on.

It's voice, LLM applications, and data pipelines in one product.

This role covers the best parts of the modern AI stack, and your fingerprints will be on all of it.

What You'll Do

• Build real-time voice agents (LiveKit, Pipecat, Twilio, Deepgram, ElevenLabs) that hold natural interviews at scale

• Design agentic LLM workflows and agent harnesses on OpenAI, Anthropic, and Google Gemini models: prompts, structured outputs, and evals

• Ship full-stack features end-to-end in Python/FastAPI and TypeScript/React

• Build pipelines that turn thousands of conversations into themes, quotes, and recommendations

• Make non-deterministic systems behave in production: observability, evals, guardrails

• Help shape engineering culture, tooling, and architecture as one of the first engineers

What We're Looking For

• Strong engineering fundamentals and experience shipping production systems end-to-end

• Hands-on LLM experience (prompting, structured output, retrieval, evals) beyond demos

• Proficiency in Python and TypeScript, comfort across backend and frontend

• Bias to ship: you own problems end-to-end and iterate fast with real users

• Care for the humans behind every signal

Nice to Have

• Real-time voice or audio experience (LiveKit, Pipecat, WebRTC, telephony, STT/TTS)

• Data pipeline or analytics engineering experience

• Early-stage startup experience or 0-to-1 product ownership

Benefits

• Meaningful equity and competitive pay

• Medical, dental, and vision for you and your dependents

• Flexible time off and supportive parental leave

• Bright NYC office, team meals, offsites, and customer travel

• Learning budget and top-tier gear

Why Join Arbor:

1. Huge market, weak competition: Billions of offline conversations happen daily. No one else is solving this for real enterprise.

2. Large enterprise customers: We're already working with multi-billion dollar manufacturers, retailers, and logistics companies.

3. Strong founding team: Backgrounds from Harvard, Princeton, Meta, Insight Partners, IBM. We know how to listen, build, sell, ship, scale - then iterate and accelerate.

4. Real upside: Already backed by the best with $6M+ from 645 Ventures, NextPlay Ventures (Jeff Weiner), Wisdom, and angels, but early enough for founding team members to see generational outcomes from equity.

5. Product that works: Customers see immediate ROI. Enterprise deals close fast.

Mostly importantly, join for the team. We're A+ players who live our values:

• Own the outcome: From first idea to customer impact, see it through. No hand-offs, no excuses.

• Real problems only: Find energy in work that actually matters, not in building features that sound cool but solve nothing.

• Intellectual honesty: Admit what isn't known, ask uncomfortable questions, and challenge assumptions without fear.

• Clarity through chaos: Thrive in 0-to-1, high-intensity environments. Move fast but think clearly, turn confusion into direction, ship quality under pressure.

• Empathy above all: Obsess over customer problems and think deeply about user needs before making any decision.