Lead AI Engineer (Conversational AI & LLMs)

Position Details :

Location : Hyderabad (Development Centre)

Work Mode : 5 Days WFO (Sunday & Monday week-off)

Experience Required : 5 to 8 years

Employment Type : Full-Time (Permanent)

Notice Period : 0 to 15 Days (Immediate joiners highly preferred)

About the Client :

Our client is a well-established, US-headquartered enterprise product company with a multi-decade legacy in the communications technology space. They operate a rapidly expanding development center in Hyderabad and are currently scaling their operations targeting a 5-10x yearly growth trajectory. They offer a highly stable, product-driven engineering culture, robust employee benefits, comprehensive health insurance, and the opportunity to build cutting-edge tech from scratch.

About the Role :

We are seeking a highly skilled Lead AI Engineer to architect and build next-generation conversational AI, voice AI, and autonomous agent systems. In this role, you will spearhead the development of AI-powered enterprise applications using state-of-the-art Large Language Models (LLMs), real-time audio streaming, and Retrieval-Augmented Generation (RAG) pipelines. You will be responsible for optimizing models for latency, token efficiency, and accuracy while collaborating closely with cross-functional product and DevOps teams to integrate these solutions into core enterprise platforms.

Key Responsibilities :

- Design and develop highly scalable AI-powered enterprise applications using LLMs.

- Build Voice AI solutions optimized for real-time, low-latency conversational systems.

- Develop autonomous AI Agents capable of reasoning, planning, and executing complex tool-calling workflows.

- Design, build, and implement highly efficient RAG pipelines utilizing advanced vector databases.

- Integrate AI services seamlessly with REST APIs, WebSockets, SIP, and existing enterprise infrastructure.

- Develop and maintain highly scalable backend microservices using Python.

- Optimize all AI applications and workflows for latency, token cost reduction, and response accuracy.

- Evaluate, benchmark, and integrate emerging AI frameworks and models into the production stack.

Required Technical Expertise :

- Programming & Backend : Expert-level proficiency in Python (Mandatory). Strong hands-on experience with FastAPI, Django, REST APIs, WebSockets, Asyncio, and Microservices architecture.

- Large Language Models (LLMs) : Proven experience with OpenAI APIs, GPT-4o/GPT-5, and Claude. Deep understanding of Prompt Engineering, Function/Tool Calling, Structured Outputs, JSON Schema, Context Window Management, Token Optimization, and Model Evaluation.

- Voice AI : Hands-on experience with Speech-to-Text (STT), Text-to-Speech (TTS), OpenAI Realtime API, Streaming Audio, Voice Activity Detection (VAD), and Realtime WebSocket APIs.

- RAG & Databases : Strong experience building RAG systems utilizing Embeddings and Vector Databases (Redis, Pinecone, Weaviate, Qdrant, or Milvus).

- AI Libraries & Frameworks : Proficiency with the OpenAI SDK, LangChain, LlamaIndex, Hugging Face Transformers, Sentence Transformers, and Pydantic AI.

Preferred Qualifications (Good-to-Have) :

- Strong domain experience in Conversational AI, Voice AI, AI Assistants, Customer Support Automation, or Workflow Automation.

- Familiarity with JavaScript or TypeScript.

- Hands-on experience with the Gemini ecosystem.

- Knowledge of MCP (Model Context Protocol), AI Guardrails, Prompt Versioning, Cost Optimization strategies, and AI Evaluation Frameworks.

Interview Process & Logistics :

- Round 1 : Technical Coding Assessment

- Round 2 : Technical Interview (Face-to-Face)

- Round 3 : Techno-Managerial & HR Discussion

- Office Timings : 10 : 00 AM to 7 : 00 PM