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.

You'll drive the full AI lifecycle-from architecture to deployment and optimization-delivering 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 : 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 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.