Artificial Intelligence Engineer

Our client is building the future of intelligent enterprise automation through cutting-edge AI agents powered by Large Language Models (LLMs). We empower organizations to streamline operations, enhance decision-making, and unlock new business value using Azure OpenAI, Azure Cognitive Services, and custom multi-agent systems. We focus on building scalable, responsible, and production-grade AI that transforms business processes and user interactions across industries.

Position Overview

The client is looking for a Senior AI Engineer to lead the development of sophisticated AI agents utilizing multiple LLMs, including GPT, Codex, and other foundation models. In this role, you will work on advanced decision-making systems, intelligent document understanding, language-based automation, and context-aware virtual agents. Youll drive the full AI lifecyclefrom architecture to deployment and optimizationdelivering impactful AI solutions at scale.

Key Responsibilities

• AI Agent Architecture: Design and build intelligent multi-agent systems that collaborate to complete complex business tasks using LLMs (e.g., GPT-4, Claude, PaLM, or custom models).
• LLM Integration: Fine-tune and orchestrate large language models (GPT, BERT, T5, etc.) for tasks such as document summarization, classification, conversational AI, and dynamic decision-making.
• Cognitive Services: Leverage Azure Cognitive Services (Form Recognizer, Text Analytics, Speech-to-Text, Translator) to enhance language understanding, voice input, and multilingual capabilities.
• MLOps & Automation: Build end-to-end pipelines for continuous model training, evaluation, and deployment using Azure Machine Learning, CI/CD, and monitoring frameworks.
• Cloud-Native AI Systems: Deploy and scale AI solutions using distributed architectures on Azure, ensuring high availability, latency optimization, and compliance.

• Cross-Functional Collaboration: Work with product, engineering, and design teams to integrate AI agents into enterprise workflows and customer-facing platforms.
• Custom Model Training: Develop domain-adapted models using fine-tuning, transfer learning, and embeddings with frameworks like Hugging Face Transformers, PyTorch, or TensorFlow.
• Secure AI Development: Follow best practices in model governance, data privacy, and security (e.g., SOC 2, GDPR) to build safe and compliant AI systems.

Required Qualifications

• Education: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Experience: 5+ years of experience in building and deploying AI/ML models in production environments.
• LLM Expertise: Deep experience working with GPT (OpenAI, Azure OpenAI), Transformers, and NLP architectures for language understanding and generation.
• Cloud Skills: Proficiency with Azure cloud services, especially Azure Cognitive Services, Azure Machine Learning, and Azure OpenAI.
• Programming:

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  Strong Python development skills with hands-on experience in frameworks such as PyTorch, TensorFlow, and Hugging Face.
• MLOps: Experience with CI/CD for ML, model versioning, automated retraining, and real-time model monitoring.
• APIs & Integration: Proficiency in RESTful API development and integrating AI into external systems and UIs.
• Security & Compliance: Understanding of AI governance and data protection requirements for deploying AI at scale.

Preferred Qualifications

• Knowledge of RAG architectures, agentic systems, or prompt engineering at scale.
• Open-source contributions or research in NLP, ML, or generative AI.
• Experience with multilingual AI, speech recognition, or custom embeddings.