- Salary
- $100k – $130k/yr
- Location
- New York, New York, US
- Workplace
- Hybrid, Onsite
- Type
- Full-time
- Department
- Engineering
- Source
- Y Combinator
Description
Location: Hybrid- NYC (3+ days in office required)
Type: Full-time W-2 employee, subject to a 90-day introductory period
Salary and equity commensurate with experience and performance
About AviaryAI
We build AI voice agents for banks, credit unions, and insurers.
Our agents are live and handling real customer calls today. We’re backed by Y Combinator and growing.
We started with voice. Our SMS and RCS agents began as clones of the voice product — and they’re growing fast. Messaging is becoming a major part of our platform, and it needs a dedicated owner
The Role
You’ll be a full stack engineer working across our platform — and you’ll head the engineering effort on our SMS and RCS expansion.
This means:
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Leading the engineering effort to evolve our SMS and RCS agents from voice-agent clones into a messaging-native product — rich cards, suggested replies, media, session handling
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Writing the backend logic that manages conversation state and decision-making (Python)
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Building internal dashboards and tools to configure and debug agents (TypeScript)
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Contributing to our core frontend application as needed
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Integrating with messaging providers and carrier infrastructure — delivery, 10DLC, opt-in/opt-out
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Debugging real production issues when things break
You’ll own the messaging vertical from prototype to high-volume production.
This is not a ticket-driven role. You’ll have a lot of responsibility and a lot of autonomy.
What We’re Looking For
- 1–3 years full stack experience (new grads welcome)
- Strong in Python
- Comfortable in TypeScript / modern frontend frameworks
- Experience building systems with real state or multi-step workflows
- Comfortable integrating third-party APIs
- Able to work without detailed specs
Bonus if you’ve worked in:
- Startups
- Fintech / insurance
- Messaging or telephony systems (Twilio, Telnyx, Bandwidth, SMS compliance)
- LLM applications (prompting, agent frameworks, evals)
What This Is Like
You won’t just be building CRUD endpoints.
You’ll be building systems that:
- Decide what to say next in a live conversation — hours or days after the last message
- Enforce business rules and compliance requirements (TCPA, carrier filtering, quiet hours)
- Handle messy, real-world edge cases
- Run thousands of concurrent conversations reliably
Your code will power real conversations with real customers — and unlike voice, every word is in writing.
