"Only Male candidates are preferred for this role"

Prospect Description Lead AI Engineer

Our end client a research and technology-driven organization focused on Artificial Intelligence, Machine Learning, computer vision, and advanced software solutions develops innovative, AI-powered technologies and intelligent systems for real-world applications. The organization combines research expertise with strong engineering capabilities to deliver scalable, next-generation AI solutions.

They are looking for an experienced Lead AI Engineer to drive the design, development, and deployment of advanced AI solutions. This is a high-impact opportunity for professionals who enjoy solving complex AI challenges, leading technical initiatives, and building innovative, production-ready intelligent systems.

Role & responsibilities

- Design and develop AI-powered enterprise applications using LLMs.
- Build Voice AI solutions for real-time conversational systems.
- Develop AI Agents capable of reasoning, planning, and tool execution.
- Design and implement RAG pipelines using vector databases.
- Integrate AI services with REST APIs, WebSockets, SIP, and enterprise

systems.

- Develop scalable Python microservices.
- Optimize AI applications for latency, cost, and accuracy.
- Build reusable AI workflows and tool-calling frameworks.
- Collaborate with Product, QA, and DevOps teams.
- Evaluate and integrate emerging AI technologies.

Required candidate skills

Programming Languages





- Python (Mandatory)
- JavaScript/TypeScript (Preferred)
- Database [Vector DB]

Backend Development

- FastAPI
- Django
- REST APIs
- WebSockets
- Async Programming (asyncio)
- Microservices
- Redis

1. Large Language Models (LLMs)

Must have experience with:

- OpenAI APIs (Chat Completions / Responses API)
- GPT-4o / GPT-5 or equivalent LLMs
- Claude
- Gemini (Preferred)

Good understanding of:

- Prompt Engineering
- Function Calling / Tool Calling
- Structured Outputs
- JSON Schema
- Context Window Management
- Token Optimization
- AI Safety
- Model Evaluation

2. Voice AI

Hands-on experience with:

- Speech-to-Text (STT)
- Text-to-Speech (TTS)
- OpenAI Realtime API (Preferred)
- Streaming Audio
- Voice Activity Detection (VAD)
- Realtime WebSocket APIs

3. Retrieval-Augmented Generation (RAG)

Experience with:

- Embeddings
- Vector Databases

Preferred databases:

- Redis Vector Search
- Pinecone
- Weaviate
- Qdrant
- Milvus

AI Libraries & Frameworks

Strong experience with:

- OpenAI SDK
- LangChain
- LlamaIndex
- Hugging Face Transformers
- Sentence Transformers
- Pydantic AI (Preferred)

Preferred Domain Experience

- Conversational AI
- Voice AI
- AI Assistants
- Customer Support Automation
- Workflow Automation

Nice to Have

- MCP (Model Context Protocol)
- AI Guardrails
- Prompt Versioning
- Cost Optimization
- AI Evaluation Frameworks

📌 Lead AI Engineer (Hyderabad)
🏢 hiringhood
📍 Hyderabad