AI​/GenAI Architect

Purple Drive

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:

• Speech APIs (Azure Speech, Amazon Transcribe, Google Speech-to-Text)
• Chat platforms (Teams, Slack, web chat widgets)
• 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 GCP (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.