Description Location: Hyderabad

Experience: 5–8 years

Role: Senior AI/ML Engineer – Conversational AI & Voice Analytics

About the Role

We are looking for an experienced AI/ML Engineer with strong expertise in NLP, NLU, Conversational AI, Voice/IVR systems, and Generative AI to build intelligent, production-grade conversational and voice solutions.

The ideal candidate will have hands-on experience working with speech and language technologies, including intent recognition, entity extraction, speech-to-text, text-to-speech, voice analytics and conversational systems, along with the ability to integrate LLMs and GenAI into enterprise applications.

You will be responsible for designing and developing AI solutions that can understand customer conversations, analyze voice data, automate interactions and generate meaningful insights from large volumes of conversational data.

Minimum Years Of Experience 5 Maximum Years Of Experience 8 Roles &

Responsibilities

Key Responsibilities

- Design, develop and deploy production-grade NLP, NLU and Conversational AI solutions.
- Build intelligent chatbots, virtual assistants and voicebots capable of handling multi-turn conversations and contextual interactions.
- Develop and optimize intent classification, entity recognition, dialogue management and context-handling capabilities.
- Work with IVR and voice-based systems to automate customer interactions and improve conversational experiences.
- Build solutions involving ASR (Automatic Speech Recognition / Speech-to-Text) and TTS (Text-to-Speech) technologies.
- Analyze large volumes of voice and call-center data to derive insights around customer sentiment, intent, conversation quality and agent performance.
- Develop capabilities such as call transcription, summarization, sentiment analysis,



conversation analytics and automated quality monitoring.
- Leverage LLMs and Generative AI to enhance conversational experiences and voice analytics.
- Design and implement RAG-based conversational applications, prompt engineering, grounding and hallucination mitigation techniques.
- Explore and implement AI agents, tool/function calling and agentic workflows for conversational use cases.
- Integrate AI models with enterprise applications, APIs, databases and downstream systems.
- Evaluate and benchmark NLP, speech and LLM models for accuracy, latency, cost and overall business performance.
- Develop scalable APIs and production-ready AI services using Python and modern AI/ML frameworks.
- Collaborate with product, engineering and business teams to translate business requirements into scalable AI solutions.
- Ensure solutions are production-ready with appropriate monitoring, evaluation, security and performance optimization.

Required Skills

NLP / NLU
- Strong hands-on experience in Natural Language Processing and Natural Language Understanding.
- Experience with intent classification, entity extraction, text classification, sentiment analysis and semantic similarity.
- Good understanding of transformers, embeddings and language models.

Conversational AI
- Experience building chatbots, conversational AI platforms, virtual assistants or voicebots.
- Strong understanding of dialogue management, context, conversation flows and multi-turn interactions.




- Experience with platforms/frameworks such as Rasa, Dialogflow, Microsoft Bot Framework or equivalent is desirable.

Voice / Speech AI
- Hands-on experience with ASR/STT and TTS technologies.
- Experience with IVR, Voice AI, speech analytics or contact-center solutions.
- Understanding of call transcription, conversation analytics, sentiment/emotion analysis and voice-data processing.

Generative AI
- Robust understanding of LLMs and Generative AI.
- Hands-on experience with RAG, prompt engineering, embeddings, vector databases and LLM evaluation.
- Experience with frameworks such as LangChain, LlamaIndex or Hugging Face.
- Exposure to AI agents, function calling and agentic workflows is an advantage.

Programming & Engineering
- Strong proficiency in Python.
- Experience building REST APIs using FastAPI, Flask or equivalent.
- Experience with databases and data-processing frameworks.
- Good understanding of software engineering, Git, testing and production deployment.

Cloud & Deployment
- Experience deploying AI/ML solutions on Azure, AWS or GCP.
- Experience with Docker/Kubernetes and production-grade deployment is desirable.
- Understanding of model monitoring, observability, scalability and performance optimization.

Good to Have

- Experience in Contact Center AI / Customer Experience Analytics.
- Experience with platforms such as Azure AI Speech, Azure OpenAI, Google Speech-to-Text, Google Dialogflow, Amazon Connect or equivalent.
- Experience with multilingual conversational AI.
- Experience handling large-scale voice/call datasets.
- Experience fine-tuning or adapting LLMs, NLP or speech models.
- Knowledge of responsible AI, privacy and security considerations for conversational/voice data.

📌 Senior AI/ML Engineer – Conversational & Voice AI (Telangana)
🏢 Tiger Analytics
📍 Telangana