Lead AI Engineer, UAE

KEY RESPONSIBILITIES:

• Solution Design: 
• Drive the architecture and solution design for the AI platform, ensuring it meets business, performance, and scalability requirements 
• Design patterns for prompt-driven UI generation, long-term memory usage, and multi-agent collaboration 
• Select appropriate frameworks and orchestrators (e.g., LangChain, LangGraph, CrewAI, Agno) based on project needs 


• Application Development: 
• Build and maintain production-grade agentic AI services in Python 
• Own integration patterns between schema-rendered UI, prompt handling, and inference pipelines 
• Implement APIs and backend components to interface with LLMs, memory stores, external tools, and enterprise systems 
• Develop and integrate RAG pipelines, vector stores, and structured output parsing 
• Contribute to re-usable libraries and accelerators 
• Write clean, testable code and ensure robust CI/CD and deployment pipelines are in place 


• Technical Leadership:  
• Provide technical guidance to junior and mid-level developers 
• Conduct code reviews and maintaining high standards of software quality 
• Collaborate closely with product managers, front-end developers, and Lab49’s and Client’s architecture and QA teams 
• Stay current with the rapidly evolving LLM landscape and proactively suggest innovations 

EXPERIENCE AND SKILLS:

• Required experience and skills:  
• Bachelor's degree in Computer Science, Information Technology, or a related field. Master’s degree is preferred
• 5 to 10 years of hands-on software engineering experience 
• Strong expertise in Python and modern backend development practices 
• At least 2 years implementing LLM and Agentic AI solutions 
• Proven delivery of production-grade conversational AI platforms or prompt-native experiences (e.g., chatbots, voice assistants, agentic workflows) 
• Solid understanding of cloud-native AI services, preferably on AWS 
• Experience working in an agile, product-oriented delivery environment 


• Desired experience and skills: 
• Experience with RAG architectures, information extraction, and vector databases is desirable 
• Experience with Agno is a strong plus.