AI Engineering Lead

Role overview

This opportunity is for an AI Engineering Lead in Saudi Arabia, hired through a partner organization that handles applications and all subsequent recruitment steps. The position combines hands-on AI engineering with technical leadership in a fast-changing environment.

You will guide the design and delivery of advanced AI solutions, set engineering standards, and help teams turn sophisticated AI ideas into practical products with clear business impact. The role spans generative AI, machine learning systems, retrieval-augmented generation, agentic workflows, and cloud-native architectures.

This is a high-impact leadership role for someone who enjoys mentoring engineers, shaping technical direction, and building scalable systems that create measurable value.

Key accountabilities

• Build, coach, and grow a strong AI engineering team while encouraging innovation, teamwork, and high technical standards.
• Act as the main technical lead for AI programs, advising on architecture, implementation choices, and engineering practices.
• Deliver production-grade AI solutions such as machine learning systems, generative AI products, RAG platforms, and agent-based workflows.
• Convert complex technical ideas into practical guidance for both technical teams and non-technical stakeholders.
• Support clients and internal teams with AI strategy, solution planning, technology decisions, and delivery execution.
• Define and champion standards for AI-first development, cloud deployment, code quality, security, scalability, and operational reliability.
• Manage multiple AI projects and keep delivery aligned with business goals and quality expectations.
• Assess new and emerging technologies to find opportunities for improving products, services, and engineering processes.
• Work across functions to ensure AI solutions are deployed efficiently, adopted successfully, and continuously improved.

Required experience and expertise

• Deep practical experience creating, building, and deploying AI and machine learning systems in production.
• Strong command of Python and modern AI frameworks, tools, and libraries.
• Hands-on background with LLM applications, RAG systems, AI agents, and AI-powered microservices.
• Working knowledge of tools and platforms such as LangChain, LlamaIndex, vector databases, PyTorch, TensorFlow, Docker, Kubernetes, and cloud providers like AWS, Azure, or Google Cloud.
• Solid understanding of MLOps, LLMOps, CI/CD workflows, model observability, monitoring, performance tuning, latency reduction, and cost management.
• Proven ability to lead, mentor, or manage engineering teams in technically complex settings.
• Experience designing cloud architectures that are scalable, secure, and maintainable.
• Strong consulting ability, stakeholder management skills, and confidence in client-facing conversations.
• Ability to explain trade-offs and strategic choices clearly to audiences with different levels of technical knowledge.
• Genuine interest in continuous learning and staying current with AI and software engineering advances.

Benefits and working environment

• Fully remote setup with flexibility and better work-life balance.
• Chance to lead innovative AI initiatives using current methods and technologies.
• Meaningful influence over technical strategy, engineering standards, and company growth.
• Exposure to varied client work and challenging AI problems across industries.
• A collaborative, highly capable engineering culture centered on innovation and improvement.
• Professional growth through exposure to emerging AI technologies and leadership responsibilities.
• Room for career advancement in a fast-growing AI-focused organization.
• Entrepreneurial environment that rewards ownership, creativity, and impact.
• Competitive compensation aligned with experience and expertise.
• Opportunity to contribute to transformative projects shaping the future of AI-driven solutions.

Recruitment and data processing details

Applications are reviewed and managed by the partner company, which also handles the next steps in the hiring process. An AI-assisted matching workflow may be used to assess applications against the role’s core requirements and create a shortlist for the hiring team. Final decisions, interviews, and assessments are conducted by the employer’s internal team.

By applying, candidates acknowledge that personal data may be processed to evaluate candidacy and shared with the hiring employer for recruitment purposes. The processing is based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. Applicants may exercise data rights such as access, correction, deletion, and objection at any time.

AI tools may support parts of the recruitment process, including resume review, response analysis, and the identification of potential inconsistencies or verification signals. These tools assist recruiters but do not replace human judgment, and final hiring decisions remain with people.