AI Engineer

AceNet; Abu Dhabi Emirate; Hybrid; AED 400,000 - 700,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive employee benefits

Learning and development opportunities

Career growth culture

Job summary

AceNet in the United Arab Emirates is seeking an experienced AI/LLM developer to design and ship AI-powered solutions. You will build real-time voice and conversational AI applications using Pipecat AI, integrate OpenAI APIs, and deploy LLM-based assistants and chatbots across enterprise contexts.

The role requires hands-on experience with REST APIs, backend services, prompt engineering, and integrating AI with external data sources.

Qualifications

• Bachelor's degree or higher in Computer Science, IT, Engineering, or related field.
• Minimum 3 years of hands-on AI/LLM development experience.
• Hands-on experience with Pipecat AI for real-time voice AI and conversational apps.
• Strong understanding of LLMs and OpenAI APIs integration.
• Experience building conversational AI, voice assistants, AI agents, and chatbots.

Responsibilities

• Build and integrate AI solutions using OpenAI APIs and LLMs.
• Develop real-time voice AI and conversational apps with Pipecat AI.
• Design and implement LLM-based applications, AI agents, chatbots, and interfaces.
• Integrate REST APIs and backend services to support AI apps.
• Apply prompt engineering to improve LLM accuracy and relevance.
• Collaborate with stakeholders and teams to deliver AI solutions.

Skills

Analytical skills

Problem-solving

Communication skills

Independent work

Cross-functional collaboration

Education

Bachelor's degree or higher in Computer Science or related field

Tools

Pipecat AI

LangChain

LangGraph

LlamaIndex

Pinecone

FAISS

ChromaDB

Weaviate

Job description

Key Responsibilities:

• Build and integrate AI solutions using OpenAI APIs, Large Language Models (LLMs), and related AI technologies.
• Develop real-time voice AI and conversational AI applications using Pipecat AI.
• Design, develop, and implement LLM-based applications, AI agents, chatbots, and conversational interfaces.
• Build and integrate voice-based AI solutions with LLMs, speech-to-text (STT), and text-to-speech (TTS) services.
• Develop and integrate REST APIs and backend services to support AI-powered applications.
• Implement prompt engineering techniques to improve LLM response accuracy, relevance, and overall performance.
• Integrate AI applications with external APIs, databases, and enterprise backend systems.
• Explore and implement Retrieval-Augmented Generation (RAG) solutions for context-aware AI applications.
• Test, troubleshoot, and optimize AI applications for performance, scalability, reliability, and response quality.
• Independently handle assigned technical development activities, debugging, integration, and deployment.
• Collaborate with business stakeholders, architects, and development teams to understand requirements and deliver effective AI solutions.
• Stay updated with emerging AI technologies, LLM frameworks, conversational AI platforms, and industry best practices.

Role Requirements and Qualifications

• Bachelor's degree or higher in Computer Science, IT, Engineering, or a related field.
• Minimum 3 years of relevant hands‑on experience in AI/LLM development.
• Practical hands‑on experience with Pipecat AI for developing real‑time voice AI and conversational applications.
• Strong understanding of Large Language Models (LLMs) and hands‑on experience integrating OpenAI APIs.
• Experience developing conversational AI applications, voice assistants, AI agents, and chatbot solutions.
• Good understanding of REST APIs, backend development, and third‑party API integrations.
• Experience with prompt engineering and LLM response optimization.
• Understanding of real‑time communication, voice processing, and conversational workflows.
• Ability to troubleshoot, debug, and optimize AI‑powered applications.
• Strong analytical, problem‑solving, and communication skills.
• Ability to work independently and collaborate effectively with cross‑functional teams.

Preferred Qualifications

• Experience implementing Retrieval-Augmented Generation (RAG) architectures.
• Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, or Weaviate.
• Experience with speech‑to‑text (STT) and text‑to‑speech (TTS) technologies.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar LLM frameworks.
• Experience developing real‑time voice agents and low‑latency conversational AI systems.
• Knowledge of WebSockets, WebRTC, and real‑time streaming technologies.
• Experience with cloud platforms such as AWS or Azure.
• Understanding of AI agent architectures, tool calling, and function calling.
• Experience with Docker, microservices, and application deployment.
• Familiarity with Agile/Scrum methodologies.

Why Join Us:

• Opportunities to work on transformative AI and Generative AI projects with leading global organizations.
• Continuous investment in learning, upskilling, and professional development.
• Collaborative work environment with experienced technology professionals.
• Competitive compensation and comprehensive employee benefits.
• A culture that encourages innovation, ownership, and career growth.