Lead AI Engineer

Lead AI Engineer

About the Role

Tech Lead

This is a player-coach role. Youll write code, make architectural decisions, and set the technical bar for how we build intelligent, low-latency voice agents.

What Youll Own

Agent Loop & Reasoning

• Design the agentic runtime that powers natural, multi-turn conversations while executing complex business logic (payment negotiations, compliance guardrails, objection handling)


• Build primitives that balance conversational fluidity with structured reasoning-the agent needs to feel human while making verifiable decisions


• Create context management systems that track consumer state, conversation history, and business rules across long, branching dialogues

Voice AI Systems

• Architect our real-time voice pipeline for sub-1s latency across transcription, reasoning, and synthesis


• Own VAD tuning, and turn-taking logic that makes conversations feel natural


• Evaluate and integrate speech models (STT, TTS, speech-to-speech) as the landscape evolves-we currently work with ElevenLabs and Cartesia for Text to Speech, and Deepgram for Speech to Text, and are always exploring whats next


• Debug and optimize streaming audio and WebRTC

LLM Infrastructure

• Design our prompting, orchestration, and model routing strategies


• Build evaluation frameworks that measure agent quality beyond accuracy-conversation quality, empathy, compliance adherence


• Stay current on model capabilities and make pragmatic build-vs-integrate decisions

Technical Leadership

• Set architectural direction for proAgent platform and surrounding applications


• Mentor engineers and establish engineering practices that scale


• Partner with Product and Client teams to translate customer problems into technical roadmaps


• Make tradeoffs between shipping fast and building durable systems-we need both

What You Bring

• 4+ years

  building production systems, with

  1+ years

  in a Lead for a project


• Hands-on work with

  LLMs in production

  : prompt engineering, orchestration, evaluation


• High bias for action to see things to production - real-time systems can get gnarly, and truly high bias is needed to take things to production


• Strong fundamentals in

  Python

  and

  TypeScript



• Clear technical communication-you can explain complex tradeoffs to engineers and stakeholders alike

Even Better

• Experience with

  voice AI

  : speech recognition, synthesis, telephony systems


• Background in

  fintech, lending, or collections



• Experience with

  Twilio, LiveKit, ElevenLabs

  , or similar real-time infrastructure


• Youve built

  agentic systems

  that combine LLM reasoning with structured actions


• Track record of

  building and scaling small teams

Why This Role

• High leverage

  : proAgent is poised to handle millions of live consumer conversations every day. Your architectural decisions directly impact business outcomes.



• Frontier work

  : Voice AI that reasons, decides, and acts is one of the hardest problems in applied AI. Were building it.



• Ownership

  : Small team, big scope. Youll shape what proAgent becomes.