Job Title

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 OverviewThe 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. You’ll drive the full AI lifecycle—from architecture to deployment and optimization—delivering impactful AI solutions at scale.Key ResponsibilitiesAI 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 QualificationsEducation: Bachelor’s or Master’s 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: 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 QualificationsKnowledge 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.