Lead AI Engineer, UAE
ION
Date: 9 hours ago
City: Dubai
Contract type: Full time

Lab49 is an NYC-based award-winning global specialist consultancy that creates bespoke technology.
Lab49 is hiring a Lead AI Engineer for an exciting opportunity in one of the world's most dynamic business hubs. This is a chance to join a pioneering team that is setting new benchmarks in the use of agentic AI, prompt-driven UIs, and LLM-powered services for a high-impact B2C client in Dubai.
Job Summary
As a Lead AI Engineer, you will play a pivotal role in the design and implementation of a complex, agentic AI–based solution for a major B2C company in Dubai, a market leader in its sector.
The platform will deliver omni-channel, prompt-driven AI services, leveraging LLMs, agentic orchestration, retrieval-augmented generation (RAG), and tight integration with the client’s existing digital and enterprise systems.
You will lead architectural decisions, guide development standards, and help shape the next-generation customer experience powered by intelligent, modular agents.
Key Responsibilities
Lab49 is hiring a Lead AI Engineer for an exciting opportunity in one of the world's most dynamic business hubs. This is a chance to join a pioneering team that is setting new benchmarks in the use of agentic AI, prompt-driven UIs, and LLM-powered services for a high-impact B2C client in Dubai.
Job Summary
As a Lead AI Engineer, you will play a pivotal role in the design and implementation of a complex, agentic AI–based solution for a major B2C company in Dubai, a market leader in its sector.
The platform will deliver omni-channel, prompt-driven AI services, leveraging LLMs, agentic orchestration, retrieval-augmented generation (RAG), and tight integration with the client’s existing digital and enterprise systems.
You will lead architectural decisions, guide development standards, and help shape the next-generation customer experience powered by intelligent, modular agents.
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
- 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.
- Details of the hybrid model: the team normally meets for 2 days a week in the office, client work may require more presence on the client premises, especially during the integration, testing and release phases of a project
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