Principal AI Engineer (Voice Bot, Agentic AI)

Role & 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 assistPrototype emotion recognition, contextual agent replies, and real-time assist layerBuild and maintain inference pipelines using FastAPI, Docker, KubernetesIntegrate AI modules into core product features (Dialer, CRM sync, IVR)Optimize model latency and deployment strategy for high concurrency environmentsArchitect scalable data pipelines using PostgreSQL, Redis, and KafkaBuild ETL/ELT workflows to support real-time analytics, dashboards, and feedback loopsMaintain secure, compliant data storage, retrieval, and access control pipelines (DPDP, GDPR-ready)Collaboration & LeadershipWork 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 standardsContribute to AI strategy, model governance, and data infrastructure roadmap Ideal Candidate Strong Principal AI Engineer (Agentic AI / Voice Bot / LLM Engineering) ProfilesMandatory (Experience 1) Must have 8+ years of overall software engineering experience, with at least 5+ years of hands-on experience in Artificial Intelligence, Machine Learning, Generative AI, or Applied AI engineering roles.Mandatory (Experience 2) Must have strong hands-on experience designing, developing, and deploying AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and Generative AI architectures.Mandatory (Experience 3) Must have minimum 1+ year of recent hands-on experience in Voice Bot Development, Voice AI, Conversational AI, AI Voice Agents, Speech AI, Contact Center Automation, or Voice Automation Platforms.Mandatory (Experience 4) Must have strong expertise in Python and should have built scalable AI/ML applications, APIs, microservices, or backend systems using Python-based frameworks.Mandatory (Experience 5) Must have hands-on experience with AI/LLM frameworks such as LangChain, LangGraph, Hugging Face, LlamaIndex, CrewAI, AutoGen, Whisper, OpenAI SDKs, or equivalent GenAI development frameworks.Mandatory (Notice Period) Immediate Joiners or candidates who can join within 15 days will be highly preferred.Preferred (Cloud) Experience with AWS, Azure, GCP, MLOps, AI deployment platforms, model serving infrastructure, and cloud-native architectures. Perks, Benefits and Work Culture Shape the AI-native dialer experience agents across India and OverseesBuild with purpose multilingual, affordable, fast-deploy SaaS platform for emerging marketsWork with modern tech: GPT, Whisper, LangChain, WebRTC, React, FastAPI Skills: pipelines,ml,bot,infrastructure,ai,learning,automation Role & 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 assistPrototype emotion recognition, contextual agent replies, and real-time assist layerBuild and maintain inference pipelines using FastAPI, Docker, KubernetesIntegrate AI modules into core product features (Dialer, CRM sync, IVR)Optimize model latency and deployment strategy for high concurrency environmentsArchitect scalable data pipelines using PostgreSQL, Redis, and KafkaBuild ETL/ELT workflows to support real-time analytics, dashboards, and feedback loopsMaintain secure, compliant data storage, retrieval, and access control pipelines (DPDP, GDPR-ready)Collaboration & LeadershipWork 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 standardsContribute to AI strategy, model governance, and data infrastructure roadmap Ideal Candidate Strong Principal AI Engineer (Agentic AI / Voice Bot / LLM Engineering) ProfilesMandatory (Experience 1) Must have 8+ years of overall software engineering experience, with at least 5+ years of hands-on experience in Artificial Intelligence, Machine Learning, Generative AI, or Applied AI engineering roles.Mandatory (Experience 2) Must have strong hands-on experience designing, developing, and deployin