Senior Software Engineer

Company: Arbor

Location: New York, NY

Salary: $170,000 - $220,000 a year

Type: Full-time

Posted: 2026-05-29

About this role

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

Billions of critical conversations happen every day in retail, hospitality, food service, logistics, and beyond — with customers and employees. Historically, these insights disappear the moment they're spoken.

Arbor turns in-person conversations into executive-grade strategic intelligence. We're signing real enterprise contracts in industries that power the global economy. The opportunity is massive, the problems are unsolved, and we need product-obsessed builders to join on our journey.

Must-haves

  • 5+ years shipping production software, including time as an early engineer at a seed/Series A startup
  • Full-stack generalist who owns features end-to-end with sharp product judgment — knows what to build, what to cut, when to push back
  • Ships predictably and communicates clearly; credible with an enterprise VP of Ops on a customer call and async with a remote CTO
  • Production experience in at least one of voice/audio, LLM apps, or data/insights pipelines (Umi is all three)
  • Fluent in Python/FastAPI + TypeScript/React; moves across frontend, backend, and infra in a single PR
  • Has shipped against flaky third-party APIs under latency/reliability pressure (telephony, real-time audio, payments, etc.)
  • Working knowledge of LLM app development: prompts, structured output, retrieval, evals, and non-deterministic systems that hold up in prod
  • AWS or GCP with multi-tenant SaaS security instincts (data isolation, PII, SOC 2)
  • Excited to be a foundational hire building AI for frontline enterprise

Nice-to-haves

  • Staff/tech-lead IC ready to grow into eng lead within ~12 months
  • Voice agent stack (LiveKit, Pipecat, Vapi, Retell, or custom on Twilio/Deepgram/ElevenLabs) + speech fundamentals (ASR, TTS, diarization, VAD)
  • Production agentic LLM workflows: tool use, multi-step, eval-driven
  • Data/analytics depth: warehouse modeling, DBT, owning an insights pipeline
  • On-call comfort on a s...

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