Lead AI Engineer

About the role

We are seeking a Lead AI Engineer to drive AI‑driven strategies, architectures and operating models for our engineering teams in Doha. You will shape AI adoption across the organization, ensuring scalable, secure and compliant implementations that deliver measurable business outcomes.

Key responsibilities

• Architect and deploy token‑efficient AI search and retrieval systems optimized for cost, relevance and performance.
• Advise on AI adoption strategies, including 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 (embeddings, vector stores, retrieval layers, LLM integrations, streaming inference).
• Develop operational strategies for agentic systems, covering rollout governance, versioning and observability.
• Partner with product owners and engineering leads to define AI adoption roadmaps and uplift workforce capability.
• Drive training, playbooks and mentorship to accelerate AI‑enabled engineering workflows.
• Implement responsible AI practices, ensuring compliance with security, safety and ethical guidelines.

Required profile

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

Required skills

• Python
• Java
• REST
• gRPC
• Kubernetes
• Cloud services (AWS/Azure/GCP)
• CI/CD pipelines
• Embeddings
• Vector databases
• Retrieval strategies
• LLM integration
• Streaming inference
• Agent frameworks
• AI observability
• Testing frameworks
• Model versioning
• Prompt governance

What we offer

• Private healthcare and life insurance
• End‑of‑service gratuity
• Annual air travel tickets for expatriates
• Employee referral program with rewards
• Learning and development opportunities, including in‑house training, professional certifications and courses