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 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
- Strong Principal AI Engineer (Agentic AI / Voice Bot / LLM Engineering) Profiles
- Mandatory (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 Oversees
Build with purpose — multilingual, affordable, fast-deploy SaaS platform for emerging markets
Work with modern tech: GPT, Whisper, LangChain, WebRTC, React, FastAPI
Pay: ₹1,172,548.83 - ₹2,700,000.00 per year
Application Question(s):
- What is your notice period in days? (30)
- What is your current CTC in LPA?
- What is your expected CTC in LPA? (27)
- Are you serving Notice Period or available to join within 15 days?
- Are you holding any offer in hand?
- How many years of hands-on experience do you have in Voice Bot / Voice AI development? Please share the Voice Bot use cases you have worked on?
- How many years of hands-on experience do you have in Agentic AI development? Which Agentic AI frameworks have you worked with ?
Experience:
- Overall: 8 years (Required)
- AI Engineer: 5 years (Required)
Work Location: In person
