Lead AI Engineer

Overview

We are seeking a Lead AI Engineer to join our team onsite in Doha, Qatar. This leadership position involves spearheading the design and deployment of AI-driven strategies, architectures, and models that help engineering teams evolve towards specification-driven and agentic AI development methodologies. The role is vital in steering AI-assisted software delivery, ensuring solutions are scalable, compliant, secure, and deliver measurable business value.

Key Responsibilities

• Design and implement token-efficient AI search and retrieval systems, focusing on operational cost, relevance, and performance optimization.
• Consult on AI adoption approaches, discerning optimal use cases for Retrieval Augmented Generation (RAG), autonomous agents, copilots, or traditional engineering methodologies.
• Establish and enforce specification-driven development techniques underpinned by governance and reusable standards.
• Develop and define key performance indicators to assess productivity enhancements, quality improvements, and maturity of AI adoption.
• Create comprehensive AI processing pipelines, integrating embeddings, vector databases, retrieval mechanisms, large language model (LLM) connections, and streaming inference capabilities.
• Formulate operational governance for agentic AI systems including rollout strategies, version control, and system observability.
• Collaborate closely with product managers and engineering leaders to map AI adoption roadmaps and enhance workforce capabilities.
• Lead AI education through creation of training materials, operational playbooks, and mentorship programs to boost AI proficiency in engineering workflows.
• Implement and uphold responsible AI practices ensuring adherence to security, safety, and ethical standards.

Candidate Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or related technical discipline.
• Minimum of 4 years building production-grade AI systems or at least 2 years focused on production-level LLM and RAG solutions.
• Demonstrable leadership in AI transformation projects including strategy formulation and broad adoption.
• Expert understanding of RAG architectures, including embeddings, vector databases, and retrieval methodologies.
• Strong programming proficiency in Python; familiarity with Java and API protocols such as REST and gRPC.
• Experience developing agent framework solutions and deploying agentic workflows within enterprise software contexts.
• Practical experience with Kubernetes, cloud platforms, continuous integration and deployment pipelines, and automation of deployment tasks.
• Hands-on skill integrating LLM providers and self-hosted AI models into scalable production environments.
• Knowledge of AI observability, model testing, version management, and prompt governance techniques.

Benefits and Perks

• Private healthcare coverage along with life insurance benefits.
• Entitlement to end of service gratuity payments.
• Annual airfare tickets provided for expatriate employees.
• Corporate incentive schemes including an Employee Referral Program with rewards.
• Access to continuous learning via in-house training, mentoring, professional certifications, and specialized courses.