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 8-15 years.

- Agentic AI and Voice Bot Development experience Mandatory.

- Minimum 5 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.