AI Team Lead

About this role

InnovationTeam is a forward-thinking technology company specialized in delivering advanced AI-driven solutions for enterprises and government organizations. We are currently seeking a highly skilled AI Team Lead to join our team onsite in Saudi Arabia. As an AI Team Lead at InnovationTeam, you will be responsible for leading the design, development, implementation, and delivery of end-to-end AI solutions across multiple domains, including Generative AI, machine learning, deep learning, data science, computer vision, NLP, intelligent automation, and enterprise AI systems. This role is not limited to Generative AI. It requires a strong technical background across modern AI technologies, hands-on experience in building production-ready AI solutions, and the leadership capability to manage AI engineers, data scientists, ML engineers, and cross-functional delivery teams. The ideal candidate is a strong technical leader who can translate business requirements into scalable AI solutions, manage project execution, guide technical teams, communicate with stakeholders, and ensure successful delivery of AI initiatives within scope, timeline, and quality standards. At InnovationTeam, we value innovation, ownership, collaboration, and continuous learning. We provide a dynamic work environment where technical excellence, leadership, and business impact are highly recognized. Requirements We are seeking an experienced AI Team Lead to lead onsite AI delivery in Saudi Arabia. The role involves managing AI projects, supervising technical teams, designing AI architectures, developing enterprise-grade solutions, and ensuring successful deployment of AI systems into production. The candidate should have strong experience in Generative AI, machine learning, deep learning, data science, AI solution architecture, MLOps/LLMOps, cloud deployment, and project management. Key Responsibilities Lead the AI team in designing, developing, and delivering enterprise AI solutions. Manage AI projects from requirement gathering to production deployment. Translate business needs into technical AI solution designs and implementation plans. Design and supervise solutions involving Generative AI, LLMs, RAG systems, AI agents, NLP, machine learning, deep learning, and computer vision. Lead data science initiatives, including data analysis, feature engineering, model development, evaluation, and optimization. Build and oversee end-to-end AI pipelines, including data ingestion, preprocessing, model training, inference, monitoring, and continuous improvement. Guide the implementation of machine learning and deep learning models using frameworks such as PyTorch, TensorFlow, Scikit-learn, and related tools. Supervise the development of AI agents, chatbots, recommendation systems, classification models, predictive analytics, and intelligent automation solutions. Define AI architecture, integration patterns, APIs, microservices, and deployment strategies. Ensure AI solutions are scalable, secure, reliable, cost-efficient, and production-ready. Collaborate with business stakeholders, product teams, data teams, software engineers, and cloud teams. Manage task allocation, technical reviews, project milestones, risks, and delivery timelines. Establish best practices for MLOps, LLMOps, model governance, model monitoring, documentation, and quality assurance. Support presales and client discussions by providing technical input, solution proposals, effort estimation, and feasibility assessments. Ensure AI solutions comply with security, privacy, governance, and responsible AI principles. Mentor and coach AI engineers, ML engineers, data scientists, and junior team members. Stay up to date with the latest developments in AI, machine learning, deep learning, Generative AI, cloud AI services, and enterprise AI platforms. Required Skills & Qualifications Minimum 5 years of professional experience in AI, machine learning, data science, or related technology fields. Minimum 2–3 years of experience leading AI teams or managing AI solution delivery. Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computer Engineering, or a related field. Strong hands-on experience in machine learning, deep learning, NLP, Generative AI, and data science. Solid understanding of LLMs, RAG architectures, AI agents, vector databases, prompt engineering, and model evaluation. Strong experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or LlamaIndex. Experience in building and deploying ML/DL models for real-world enterprise use cases. Strong understanding of supervised learning, unsupervised learning, classification, regression, clustering, recommendation systems, forecasting, and anomaly detection. Experience with data preparation, data quality assessment, feature engineering, model training, validation, testing, and performance monitoring. Strong software engineering knowledge, including REST APIs, microservices, Docker, Kubernetes, CI/CD, and Git. Experience deploying AI workloads on cloud platforms such as OCI, Azure, AWS, or GCP. OCI experience is preferred. Knowledge of MLOps and LLMOps practices, including model versioning, monitoring, retraining, evaluation, and deployment automation. Strong project management skills, including planning, estimation, risk management, stakeholder communication, and delivery tracking. Ability to communicate complex technical concepts clearly to business and technical stakeholders. Excellent problem-solving, analytical, leadership, and decision-making skills. Excellent command of English, both written and spoken. Willingness to work onsite in Saudi Arabia. Nice to Have Experience in government, healthcare, finance, telecom, or regulated enterprise environments. Experience with GPU-based model training and inference optimization. Experience with computer vision, OCR, document AI, speech AI, or multimodal AI systems. Experience wi