Job Description

We are looking for an experienced

AI Engineer (Voice Agents) who has

designed, built, and deployed production-grade AI voice agents not just prototypes. You'll join a fast-moving, product-led team where ideas go from MVP to production in weeks, not quarters.

This is a hands-on role for someone who enjoys owning the full lifecycle architecture, modeling, evaluation, deployment, monitoring, and iteration.

What You'll Do

1. Build & Ship Voice Agents

Design, build, and deploy

inbound and outbound voice agents

for real-world business workflows. Own

E2E pipeline

-- speech-to-text, LLM reasoning, prompt strategy, dialog state management, TTS, telephony integration. Rapidly iterate MVPs and harden them to

production quality

with robust SLAs.

2. Engineering & Architecture

Architect scalable agentic systems using modern tooling (OpenAI, Anthropic, DeepSeek, Inspector, Whisper, PlayHT, ElevenLabs, PolyAI-style dialog). Implement retrieval (RAG), vector stores, and memory systems to boost accuracy in complex tasks. Integrate voice agents with

CRM, ticketing, telephony, and workflow orchestration systems

.

3. Production & Reliability

Set up observability: monitoring, logging, red-teaming, evals, hallucination detection. Drive latency reduction, call-success metrics, correctness of agent actions. Run A/B tests, fine-tuning, guardrails, fallback flows.

4. Collaboration & Product Work

Work closely with product, engineering, and domain stakeholders to define agent behavior. Translate business processes into voice agent flows that operate with high autonomy. Contribute to internal frameworks and reusable components for deploying voice agents faster.

What You Bring

4-7 years of hands-on AI/ML engineering experience.

At least one real, production-deployed AI voice agent

(inbound or outbound) that handled real customer calls. Deep expertise in: Speech-to-Text (Whisper, AssemblyAI, Deepgram, Google STT) LLMs (OpenAI, Anthropic, Llama, Gemini, DeepSeek) Text-to-Speech (ElevenLabs, PlayHT, Azure TTS) Telephony (Twilio, SIP, WebRTC, Asterisk, etc.) RAG, embeddings, vector databases Python/Node JS for AI agent orchestration Experience deploying production microservices (Docker, Kubernetes, CI/CD). Strong latency optimization + debugging skills -- especially for

real-time audio

. Ability to work in fast environments: MVP in weeks ? robust production in months.

Nice to Have

Experience with vendor ecosystems like

ElevenLabs

,

PolyAI, Sierra, Decagon, Replicant

. Experience building frameworks for agent evaluation and "reasoning trace" inspection. Background in conversation design or dialog management. Experience with reinforcement learning for dialog optimization.

Success Looks Like

In the first 2-4 months you will: Deliver at least one production-ready voice agent handling real customer traffic. Build internal tooling that reduces time to deploy new agents. Improve latency, call success rate, and downstream business outcomes. Establish metrics, dashboards, and evaluation tooling for all voice agents. Become the go-to owner for AI voice agent architecture and innovation.
_

Why Join Us

_

Work directly with experienced founders and a high-caliber product/engineering team. Own end-to-end systems with massive autonomy. Ship real products that touch thousands of customers. Opportunity to shape core AI infrastructure and voice agent strategy. Competitive compensation + high-growth environment.

How to Apply

Send your GitHub/portfolio, past projects, and a brief note on the

voice agents you've deployed

to:

jobs@vikara.ai

Required: Please create your profile on (Aithors.ai)

Job Type: Full-time

Pay: ?2,200,000.00 - ?3,500,000.00 per year

Benefits:

* Work from home