R32587 Senior AI Agent Engineer - Voice AI

The Agentic Tribe is revolutionizing the chatbot and voice assistance landscape with Gen3, a cutting‑edge AI Agent system that's pushing the boundaries of conversational AI. Gen3 is not your typical chatbot; it’s a goal‑oriented, dynamic, and truly conversational system capable of reasoning, planning, and adapting to user needs in real time. Leveraging a multi‑agent architecture and advanced language models, Gen3 delivers personalized and engaging user experiences, going far beyond scripted interactions to handle complex tasks and “off‑script” inquiries with ease.

We are seeking a passionate and experienced Senior Voice AI Agent Engineer with a strong focus on Voice AI to join our team. In this role, you will be dedicated to innovating at the forefront of conversational AI, engineering intelligent, autonomous agents that can listen, understand, and speak with human‑like fluidity.

You will build the cognitive architecture for our voice applications, creating systems that can reason, plan, and execute complex tasks through seamless, low‑latency spoken dialogue. A key part of your role will be to effectively communicate complex technical concepts to both technical and non‑technical stakeholders.

• Design and develop robust, stateful, and scalable voice‑first AI agents using Python, specifically optimized for real‑time voice interactions, managing turn‑taking, interruptions, and low‑latency responses.

• Integrate best‑in‑class real‑time Speech‑to‑Text (STT), Text‑to‑Speech (TTS), and Voice Activity Detection (VAD) services to create a seamless conversational flow.

• Connect voice agents with existing enterprise systems, databases, and third‑party APIs to create powerful, end‑to‑end automated workflows initiated and managed through voice.

• Establish and own the Evals for voice agent performance and behavior and iterate over time and systematically improve performance, reliability, and the overall user experience.

• Build end‑to‑end conversational flows with reasoning, planning, and dynamic tool use — beyond pre‑scripted voice experiences.

• Work cross‑functionally with product managers, ML scientists, and engineers to deeply understand user needs and voice interaction goals.

• Implement fallback, recovery, and error‑handling strategies to deal with noisy audio input or speech recognition inaccuracies.

• Define and track voice‑specific evaluation metrics (e.g., word error rate, latency, conversational naturalness).

• Develop observability tools and guardrails to monitor performance, ensure safety, and handle edge cases in spoken interactions.

• Document your development, architecture decisions, and research findings to share knowledge across the team.

• LLM‑Oriented System Design:
  Strong experience building multi‑step, tool‑using agents (Lang Chain, Autogen). Familiar with prompt engineering, context management, and reasoning strategies like Chain‑of‑Thought and ReAct.

• Voice AI Expertise:

  • Experience building low‑latency, streaming voice applications. Expertise in integrating and managing real‑time STT/TTS models and APIs. Proficient with techniques for Voice Activity Detection (VAD), noise suppression, and implementing robust barge‑in/interruption logic.

  • Experience with integrating third‑party voice AI APIs, including Speech‑to‑Text (STT) and Text‑to‑Speech (TTS) services from providers like OpenAI, Deepgram, Eleven Labs, etc.

  • Understanding of latency, timing, and streaming audio constraints.

• Tool Integration & APIs:
  Comfortable connecting agents to external APIs, tools, databases in secure environments.

• RAG (Retrieval‑Augmented Generation):
  Building pipelines with vector stores, chunking strategies, and hybrid retrieval.

• Evaluation & Observability:
  Implementing and using monitoring tools and evaluation frameworks (Braintrust) to score our AI Agents.

• Safety & Reliability:
  Familiarity with techniques for prompt injection defense, guardrails (Rebuff, Guardrails AI), and failover logic.

• Performance Optimization:
  Token budget and latency management using caching, model routing, etc.

• Programming & Deployment:
  Expert in Python, FastAPI, and LLM SDKs. Experience deploying AI apps to cloud platforms (AWS, GCP,…