Only Male candidates are preferred for this role.

Programming Languages :

- Python (Mandatory)

- JavaScript/TypeScript (Preferred)

- Database [Vector DB & Redis]

Backend Development :

- FastAPI

- Django

- REST APIs

- WebSockets

- Async Programming (asyncio)

- Microservices

- Redis

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

Voice AI :

Hands-on experience with :

- Speech-to-Text (STT)

- Text-to-Speech (TTS)

- OpenAI Realtime API

- Streaming Audio

- Voice Activity Detection (VAD)

- Realtime WebSocket APIs

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 Domain Experience :

- Conversational AI

- Voice AI

- AI Assistants

- Customer Support Automation

- Workflow Automation

Good to have :

- MCP (Model Context Protocol)

- AI Guardrails

- Prompt Versioning

- Cost Optimization

- AI Evaluation Frameworks

Roles & 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.