AI Systems Engineer

2 weeks ago

Bengaluru, Karnataka, India beBeeMl Full time ₹ 1,50,00,000 - ₹ 2,40,00,000

Job Summary:

We are seeking a highly experienced AI/ML systems engineer to lead the operationalization of speech AI agents in telephony environments.

This role bridges the gap between AI infrastructure, voice bot deployment, and real-time streaming operations, enabling AI models to function reliably in production use cases such as customer collections, voice-based load bookings, and conversational AI in logistics and telecom.

Key Responsibilities:

  • Design, deploy, and maintain real-time speech AI agents for telephony (inbound/outbound) using CPaaS platforms and audio pipelines.
  • Integrate ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and LLMs with voice bot workflows using WebSocket or RTP streams.
  • Collaborate closely with backend engineers and AI scientists to deploy scalable ML models into production across Kubernetes, Docker, and cloud-native environments (AWS/GCP).
  • Set up observability, logging, and monitoring of speech pipelines (latency, dropouts, stream integrity) using Prometheus, Grafana, ELK, etc.
  • Automate the ML lifecycle and CI/CD for AI models using tools like MLflow, Airflow, or Kubeflow.
  • Optimize streaming latency across ASR, LLM, and TTS chains in low-latency applications like telephony bots.
  • Ensure fault-tolerant, secure, and compliant deployment of voice-based systems using industry-standard DevOps practices.

Required Skills:

  • 8 years of experience in MLOps, AI platform engineering, or DevOps with hands-on ML deployment.
  • Experience with ASR/TTS model integration (e.g., Whisper, Amazon Polly, Google Speech API).
  • Hands-on experience deploying AI in telephony environments, with working knowledge of Asterisk, FreeSWITCH, or similar systems.
  • Solid command over WebSocket, SIP, RTP, or similar streaming protocols for voice integration.
  • Proficient with cloud services (AWS/GCP/Azure), containers (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform).
  • Experience with end-to-end CI/CD pipelines, GitOps, and model monitoring (accuracy, drift, performance).
  • Strong programming in Python and scripting to support infrastructure and integration tasks.

Nice to Have:

  • Exposure to CPaaS platforms (e.g., Twilio, Vonage, Kaleyra, Exotel) for voice bot integration.
  • Familiarity with conversational AI/NLU platforms and agentic AI frameworks.
  • Prior experience supporting AI agents in collections, logistics/freight, or telecom workflows.

What We Offer:

  • Work on next-gen AI voice agents deployed in high-impact customer environments.
  • Influence platform architecture and deliver cutting-edge infrastructure for real-time ML.
  • High-ownership, engineering-led culture with strong product alignment and technical mentorship.

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