Lead AI Engineer

We're looking for aLead AI Engineerto join our team inDoha, Qatar, in anonsite working mode.

In this role, you will lead the design and implementation of AI-driven strategies, architectures and operating models, enabling engineering teams to transition to spec-driven and agentic AI delivery methods. This is a critical position to influence and drive AI-assisted development, ensuring scalable implementations, governance and measurable business outcomes. Your expertise will shape AI adoption across the organization, balancing innovation with compliance, security and operational integrity.

Responsibilities

• Architect and deploy token-efficient AI search and retrieval systems optimized for cost, relevance and performance
• Advise on AI adoption strategies, including when to apply RAG, agents, copilots or traditional engineering approaches
• Define and implement spec-driven development practices with governance and reusable standards
• Design KPIs to measure productivity gains, quality improvements and AI adoption maturity
• Build end-to-end AI pipelines, including embeddings, vector stores, retrieval layers, LLM integrations and streaming inference
• Develop operational strategies for agentic systems, including rollout governance, versioning and observability
• Partner with product owners and engineering leads to define AI adoption roadmaps and enable workforce capability uplift
• Drive training, playbooks and mentorship to accelerate workforce readiness in AI-enabled engineering workflows
• Implement responsible AI practices, ensuring compliance with security, safety and ethical guidelines

Requirements

• Bachelor's degree in Computer Science, Software Engineering or related field
• 4+ years of experience building production AI systems or 2+ years in production-level LLM/RAG solutions
• Proven track record leading AI transformations, strategy design and adoption initiatives
• Deep expertise in RAG architectures: embeddings, vector DBs, retrieval strategies
• Strong proficiency with Python, familiarity with Java and API protocols (REST/gRPC)
• Experience with agent frameworks and implementing agentic workflows in enterprise software delivery
• Practical knowledge of Kubernetes, cloud services, CI/CD pipelines and deployment automation
• Hands-on experience in integrating LLM providers and self-hosted models into scalable architectures
• Knowledge of AI observability, testing frameworks, model versioning and prompt governance