Principal AI/ML Engineer (Voice Bot, Agentic AI)

Roles & Responsibilities This is a foundational role blending applied machine learning, LLM integration, and modern data engineering to drive real-time decisioning and automation across the platform. Key Responsibilities Lead implementation of LLM-based features: summarization, sentiment detection, auto-disposition, escalation tagging Fine-tune and evaluate models (Whisper, GPT, HuggingFace, Rasa) for vernacular (Indian) language support Build and deploy LangChain pipelines for prompt engineering, QA tagging, and agent assist Prototype emotion recognition, contextual agent replies, and real-time assist layer Build and maintain inference pipelines using FastAPI, Docker, Kubernetes Integrate AI modules into core product features (Dialer, CRM sync, IVR) Optimize model latency and deployment strategy for high concurrency environments Architect scalable data pipelines using PostgreSQL, Redis, and Kafka Build ETL/ELT workflows to support real-time analytics, dashboards, and feedback loops Maintain secure, compliant data storage, retrieval, and access control pipelines (DPDP, GDPR-ready) Collaboration & Leadership Work closely with Product, Engineering, and UX to deliver features that directly impact agent productivity Guide junior ML and data engineers; define and enforce coding/data standards Contribute to AI strategy, model governance, and data infrastructure roadmap Ideal Candidate Total experience of 6-15 years Agentic AI and Voice Bot Development experience Mandatory Minimum 3 years of experience in AI with exposure to LLMs and production-grade pipelines Hands-on with Whisper, LangChain, HuggingFace, or similar frameworks Solid Python (FastAPI preferred), SQL/PostgreSQL, and experience with RESTful APIs Proven experience with CI/CD, Docker, K3s/Kubernetes, Redis, Kafka/RabbitMQ Strong understanding of NLP/STT/TTS, summarization, and emotion tagging Ability to work in startup-paced environments with ownership mindset Bonus Skills Experience with multilingual models (Hindi, Tamil, Bengali) Exposure to Rasa, Coqui TTS, or OpenWA integrations Prior work in SaaS/Contact Center/Dialer/CRM ecosystems Familiarity with speech emotion recognition or agent coaching models Perks, Benefits & Culture Shape the AI-native dialer experience agents across India and Oversees Build with purpose multilingual, affordable, fast-deploy SaaS platform for emerging markets Work with modern tech: GPT, Whisper, LangChain, WebRTC, React, FastAPI Roles & Responsibilities This is a foundational role blending applied machine learning, LLM integration, and modern data engineering to drive real-time decisioning and automation across the platform. Key Responsibilities Lead implementation of LLM-based features: summarization, sentiment detection, auto-disposition, escalation tagging Fine-tune and evaluate models (Whisper, GPT, HuggingFace, Rasa) for vernacular (Indian) language support Build and deploy LangChain pipelines for prompt engineering, QA tagging, and agent assist Prototype emotion recognition, contextual agent replies, and real-time assist layer Build and maintain inference pipelines using FastAPI, Docker, Kubernetes Integrate AI modules into core product features (Dialer, CRM sync, IVR) Optimize model latency and deployment strategy for high concurrency environments Architect scalable data pipelines using PostgreSQL, Redis, and Kafka Build ETL/ELT workflows to support real-time analytics, dashboards, and feedback loops Maintain secure, compliant data storage, retrieval, and access control pipelines (DPDP, GDPR-ready) Collaboration & Leadership Work closely with Product, Engineering, and UX to deliver features that directly impact agent productivity Guide junior ML and data engineers; define and enforce coding/data standards Contribute to AI strategy, model governance, and data infrastructure roadmap Ideal Candidate Total experience of 6-15 years Agentic AI and Voice Bot Development experience Mandatory Minimum 3 years of experience in AI with exposure to LLMs and production-grade pipelines Hands-on with Whisper, LangChain, HuggingFace, or similar frameworks Solid Python (FastAPI preferred), SQL/PostgreSQL, and experience with RESTful APIs Proven experience with CI/CD, Docker, K3s/Kubernetes, Redis, Kafka/RabbitMQ Strong understanding of NLP/STT/TTS, summarization, and emotion tagging Ability to work in startup-paced environments with ownership mindset Bonus Skills Experience with multilingual models (Hindi, Tamil, Bengali) Exposure to Rasa, Coqui TTS, or OpenWA integrations Prior work in SaaS/Contact Center/Dialer/CRM ecosystems Familiarity with speech emotion recognition or agent coaching models Perks, Benefits & Culture Shape the AI-native dialer experience agents across India and Oversees Build with purpose multilingual, affordable, fast-deploy SaaS platform for emerging markets W