- Develop and maintain AI-powered voice agents for websites and phone-based interactions.
- Build scalable and secure backend services and APIs using Python and FastAPI.
- Integrate LLMs, speech recognition, text-to-speech, telephony, and real-time communication APIs.
- Build RAG-based systems that allow AI agents to retrieve accurate and relevant information from business knowledge bases.
- Work with FAISS, FastEmbed, embeddings, vector search, and hybrid retrieval techniques.
- Develop complete knowledge-base workflows, including document ingestion, processing, chunking, indexing, retrieval, and source validation.
- Implement techniques to improve response accuracy and minimise AI hallucinations.
- Develop multilingual conversational flows with context retention, persona management, routing, call-state management, and interruption handling.
- Build integrations for lead management, call history, transcripts, recordings, analytics, KPIs, and reporting dashboards.
- Design and maintain database-backed services using PostgreSQL and asynchronous database operations.
- Implement background jobs and object-storage solutions for application data, recordings, and other assets.
- Containerize applications and manage services using Docker and Docker Compose.
- Monitor production systems and investigate issues using logs, API traces, database records, transcripts, and service-health information.
- Develop automated tests to ensure reliability of AI responses, retrieval systems, authentication, integrations, tenant isolation, and critical application workflows.
- Release updates safely while maintaining system availability and preventing impact on existing customers.
- Prepare and maintain technical documentation, deployment instructions, troubleshooting guides, and operational runbooks.

Required Technical Skills





- Strong programming experience with Python.
- Hands-on experience with FastAPI or another modern Python backend framework.
- Good understanding of async programming, WebSockets, and real-time communication.
- Experience working with PostgreSQL and SQLAlchemy, asyncpg, or similar database technologies.
- Experience integrating LLM APIs into real-world applications.
- Strong understanding of RAG architecture, embeddings, semantic search, vector databases, and document chunking.
- Experience with one or more technologies such as FAISS, FastEmbed, Qdrant, Pinecone, or Weaviate.
- Working knowledge of Linux, Docker, Git, and application deployment.
- Ability to investigate and resolve backend and distributed-system issues.
- Positive understanding of API security, authentication, authorization, tenant isolation, and secure handling of credentials and secrets.
- Strong focus on writing clean, modular, scalable, and testable code.

Preferred Experience

- Experience working with Gemini Live, OpenAI Realtime, or other real-time AI/multimodal APIs.
- Knowledge of LiveKit, SIP, WebRTC, Twilio, Exotel, or similar voice and telephony platforms.
- Understanding of audio streaming, PCM audio, Voice Activity Detection (VAD), and real-time interruption handling.
- Experience developing conversational AI systems supporting multiple Indian or international languages.
- Familiarity with MinIO, Amazon S3, or other S3-compatible storage systems.
- Experience with React and TypeScript for voice interfaces, widgets, or dashboards.
- Experience evaluating AI conversations using transcripts, retrieval relevance, grounding, response quality, and lead-conversion metrics.
- Exposure to CI/CD pipelines, cloud infrastructure, monitoring, logging, and production incident management.

Pay: ₹8,713.93 - ₹48,783.24 per month

Work Location: Remote

📌 Voice Engineer (India)
🏢 Voicedots Infotech
📍 India