Lead AI Engineer

We are looking for an AI Engineer with hands-on experience designing and deploying scalable AI solutions. In this role, you will be part of a cross-functional team working on cutting-edge projects involving Retrieval-Augmented Generation (RAG), agentic frameworks, and end-to-end MLOps workflows. You'll take ownership of translating complex business problems into AI solutions from the ground up—from initial problem analysis and architecture design through to production deployment and monitoring. You'll play a key role in developing AI applications using modern frameworks and libraries, while applying advanced prompt engineering techniques and ensuring robust monitoring and performance tracing. Your collaboration with other engineering teams will help align innovative AI systems with broader development goals. We specifically value candidates who have transitioned from data science roles into engineering, bringing both analytical depth and production deployment expertise.

What is this position about

• Analyze business problems and design AI solutions from scratch, including architecture, approach selection, and technical feasibility assessment
• Design, develop, and deploy production-ready AI solutions with focus on scalability and reliability
• Implement Retrieval-Augmented Generation (RAG) systems and fine-tuning techniques
• Build and integrate AI frameworks and agentic systems to solve complex business problems
• Apply advanced prompt engineering techniques and output post-processing strategies
• Design and implement MLOps / LLMOps pipelines including CI / CD, model versioning, and monitoring
• Lead end-to-end project delivery and mentor junior engineers
• Work with transformer-based models and optimize LLM integration patterns
• Design APIs, microservices, and event-driven architectures for AI systems
• Collaborate across teams to translate AI capabilities into business value
• Stay current with AI trends and contribute to best practices

Qualifications

Skills Required

Agile Scrum, Monitoring, Microservices, production deployment , MLops, containerization , Python Programming, Azure Cloud Services