Voice AI Engineer

Key ResponsibilitiesDeploy, configure, and optimize Voice AI agents across cloud and on-prem environments (AWS, GCP, Azure). Collaborate with client engineering and product teams to understand requirements and integrate APIs, CRMs, and telephony systems (Twilio, Exotel, etc.). Build automation pipelines for call simulations, monitoring, and analytics. Work closely with ML and platform teams to fine-tune models and troubleshoot real-time performance issues. Implement observability dashboards, run load/performance tests, and ensure low-latency, high-availability Voice AI operation. Prepare and maintain deployment documentation, configuration manuals, and client handoff playbooks. Required SkillsProgramming: Proficiency in Python (FastAPI / Flask preferred). Cloud: Experience with AWS, GCP, or Azure (deployment, networking, monitoring). DevOps: Familiarity with Docker, CI/CD pipelines, and Git version control. Databases: Hands-on experience with SQL or NoSQL databases. APIs: Strong understanding of RESTful and WebSocket integrations. Voice/Telephony (Preferred): Exposure to Twilio, Asterisk, or WebRTC systems. Preferred QualificationsPrior experience in Conversational AI, Speech Recognition (ASR), Text-to-Speech (TTS), or Voice-enabled applications. Understanding of LLMs, real-time event streaming, or telephony AI orchestration. Excellent debugging, communication, and cross-functional collaboration abilities. Proven experience in client-facing technical implementation and solution ownership from concept to deployment.