AI / GenAI Architect

Role Summary:

We are looking for a highly experienced AI Architect specializing in Python-based AI development, Large Language Models (LLMs), and the design of chatbots and voice bots. The ideal candidate will architect enterprise-grade conversational AI solutions, ensure robust LLM performance monitoring, and drive innovation in Generative AI systems.



Key Responsibilities

LLM & Conversational AI Architecture

Architect scalable solutions using LLMs, ChatGPT-style models, and voice AI frameworks.

Design and build chatbots and voice bots using Python, ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and NLP/LLM pipelines.

Create frameworks for conversational flows, prompt engineering, retrieval-augmented generation (RAG), and context management.

Solution Development

Build end-to-end AI applications using Python, integrating with APIs, databases, and cloud-native services.

Develop modular and reusable components for LLM inference, vector search, embeddings, and model orchestration.

Integrate LLMs with enterprise systems (CRM, ticketing, case management, internal knowledge bases).

LLM Performance Monitoring & Optimization

Implement monitoring systems for latency, hallucination rate, safety compliance, drift detection, prompt performance, and model quality.

Set up continuous evaluation (CEVAL), feedback loops, and telemetry dashboards.

Optimize inference cost, token usage, model selection (small vs. large models), and caching strategies



Voice Bot & Chat Bot Engineering

Architect solutions using:

o Speech APIs (Azure Speech, Amazon Transcribe, Google Speech-to-Text)

o Chat platforms (Teams, Slack, web chat widgets)

o Telephony integrations (Twilio, Genesys, Ujet)

Ensure high accuracy in intent detection, slot filling, sentiment tracking, and multimodal interaction.

MLOps & Deployment

Implement MLOps practices including CI/CD, model versioning, A/B testing, evaluation pipelines, and governance.

Deploy models on cloud platforms such as Azure, AWS, or Google Cloud Platform (Azure preferred if using OpenAI/Azure OpenAI).

Ensure compliance with enterprise AI governance, security, and ethical AI standards



Essential Skills: AI Architect| Python| LLM| Conversational AI Architecture| voice AI frameworks| ASR (Automatic Speech Recognition) | TTS (Text-to-Speech) | and NLPLLM pipelines| Voice Bot Chat Bot Engineering.