Artificial Intelligence Engineer

Must have:

Programming Languages

• Python (Mandatory)

• JavaScript/TypeScript (Preferred)

• Database [Vector DB & Redis]

Backend Development

• Fast API

• Django

• REST APIs

• WebSockets

• Async Programming (Asencio)

• 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

• 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

• We aviate

• Qanat

• Milvus

AI Libraries & Frameworks

Strong experience with:

• OpenAI SDK

• Lang Chain

• Llama Index

• Hugging Face Transformers

• Sentence Transformers

• Pedantic 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.