We are building the next-gen AI-native, multilingual, Omni channel communication platform for emerging markets. We are looking for a hands-on AI/ML & Data Engineering Lead who will own and deliver critical components of our agent assist stack including Whisper/STT, LangChain-based summarization, emotion tagging, GPT integration, and scalable data pipelines.

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 :

AI/ML LLM/NLP :

- 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

Required Skills &

Qualifications :

- 4 years of experience in ML/AI/Data Engineering 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
- Robust understanding of NLP/STT/TTS, summarization, and emotion tagging
- Ability to work in startup-paced environments with ownership mindset

📌 eDAS - Senior AI Engineer - LLM/NLP (India)
🏢 eDAS
📍 India