Conversational AI Engineer

Company Description Novagates Official is an Intelligence Infrastructure company enabling the next generation of enterprises to transform how they operate, engage customers, and accelerate growth. Built over four years of global collaboration with more than 800 engineers across 13 countries and over 50 industry consultants, Novagates delivers a unified platform that integrates intelligent automation, commerce infrastructure, immersive experiences, and enterprise intelligence. This comprehensive infrastructure helps organizations streamline complex processes and build scalable, intelligent systems. Team members join a diverse, distributed environment focused on innovation, practical impact, and long-term partnerships with enterprise clients.

• Role Description This is a full-time remote role for a Conversational AI Engineer.

Conversational AI Engineer

We are looking for a Conversational AI Engineer to design, build, and deploy production-grade AI systems powered by Large Language Models (LLMs). The role combines conversational AI, agentic systems, backend engineering, model development, and speech technologies, with a strong focus on Arabic and regional dialects.

Responsibilities

* Design and develop conversational AI and agentic systems using frameworks such as LangGraph.

* Build LLM-powered applications using LLM APIs, prompt engineering, tool calling, structured outputs, RAG, and memory.

* Develop and integrate AI agents with backend services, databases, APIs, and enterprise systems.

* Design and implement scalable backend services and APIs using Python and FastAPI.

* Apply solid backend engineering concepts, including API design, authentication and authorization, error handling, validation, logging, caching, asynchronous processing, and service integration.

* Work with databases such as MongoDB and PostgreSQL for application data, conversation state, and AI-related data.

* Use Redis for caching, session/state management, queues, and other low-latency use cases.

* Work on LLM training and fine-tuning, including data preparation, evaluation, optimization, and experimentation.

* Deploy and operate AI models using model serving and inference technologies.

* Design scalable AI services with a focus on performance, reliability, scalability, and latency.

* Integrate Speech-to-Text (STT) and Text-to-Speech (TTS)technologies into conversational AI solutions.

* Evaluate LLMs and conversational systems using quality, accuracy, latency, and task-completion metrics.

* Collaborate with ML engineers, backend engineers, data scientists, and product teams to deliver end-to-end AI solutions.

Technical Requirements

AI & LLMs

* Strong experience in AI/ML and Generative AI.

* Hands-on experience with LLMs and LLM APIs.

* Experience building agentic applications using LangGrap or similar frameworks.

* Experience with LLM training, fine-tuning, and model evaluation.

* Good understanding of RAG, embeddings, vector search, tool calling, structured outputs, and conversational memory.

* Experience with model serving, inference, and production deployment.

Backend Engineering

* Strong Python programming skills.

* Experience building production APIs and services using FastAPI.

* Strong understanding of backend concepts, including:

* REST API design

* Async programming

* Authentication and authorization

* Request validation

* Error handling

* Service-to-service communication

* Caching

* Background jobs and queues

* Logging and monitoring

* API security

* Scalability and performance

* Experience with MongoDB and PostgreSQL.

* Experience with Redis for caching, state, queues, or other backend use cases.

* Understanding of database design, indexing, transactions, and query optimization.

Speech & Conversational AI

* Experience integrating Speech-to-Text (STT) and Text-to-Speech (TTS) systems.

* Understanding of conversational AI concepts such as multi-turn dialogue, context, memory, intent, tool use, and response generation.

Arabic Language & Domain Knowledge

Strong knowledge of Arabic and Arabic dialects is required.

The candidate should understand the differences between Modern Standard Arabic and regional dialects, including dialect-specific vocabulary, expressions, pronunciation, code-switching, and conversational patterns.

Experience with Egyptian Arabic, Gulf Arabic, Levantine Arabic, or other Arabic dialects is highly valued.

Nice to Have

* Experience with Docker and cloud deployment.

* Experience with CI/CD and production AI systems.

* Experience with GPU-based model inference or serving.

* Experience with vector databases and semantic search.

* Experience with LLM observability and evaluation frameworks.

• Experience working with Arabic speech or language datasets.