Head Artificial Intelligence

Role & responsibilities

• Define and execute the organizations AI strategy, roadmap, and implementation plan aligned with business objectives.
• Lead the design, development, and deployment of AI/ML and Generative AI solutions across business functions.
• Build and scale LLM, RAG, NLP, computer vision, predictive analytics, and AI automation use cases.
• Evaluate emerging AI technologies, models, frameworks, and platforms and identify opportunities for business adoption.
• Design scalable AI/ML architectures and establish standards for model development, deployment, monitoring, and optimization.
• Lead the implementation of MLOps/LLMOps practices, including CI/CD, model versioning, monitoring, evaluation, and lifecycle management.
• Ensure AI solutions meet requirements for accuracy, scalability, security, privacy, reliability, and responsible AI.
• Manage AI projects from ideation and PoC through production deployment and continuous improvement.
• Build, mentor, and manage a high-performing team of ML engineers, data scientists, AI engineers, and researchers.
• Collaborate with product, engineering, data, business, and executive teams to identify and prioritize AI initiatives.
• Establish AI governance, model-risk controls, data governance, and responsible AI practices.
• Track AI project performance, adoption, business impact, and ROI.
• Manage relationships with technology vendors, cloud providers, and external AI partners.
• Stay current with advances in Generative AI, LLMs, agentic AI, foundation models, and AI infrastructure.

Preferred candidate profile

• 5 to 10 years of experience in AI/ML, Data Science, Machine Learning Engineering, or related technical roles, with demonstrated experience leading AI initiatives or teams.
• Strong hands-on expertise in Python, Machine Learning, Deep Learning, Generative AI, LLMs, NLP, and AI/ML frameworks.
• Strong understanding of LLM architectures, RAG, vector databases, embeddings, prompt engineering, fine-tuning, and AI agents.
• Experience with PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain/LlamaIndex, or comparable frameworks.
• Strong knowledge of MLOps/LLMOps, model deployment, monitoring, evaluation, CI/CD, Docker, Kubernetes, and MLflow.
• Experience with AWS, Azure, or GCP and cloud-based AI/ML services.
• Understanding of data engineering, data pipelines, APIs, distributed systems, and AI infrastructure.
• Demonstrated ability to take AI solutions from PoC to production at scale.
• Strong understanding of AI governance, responsible AI, data privacy, security, and regulatory considerations.
• Excellent technical leadership, people management, communication, and stakeholder-management skills.
• Ability to translate complex AI capabilities into business solutions, measurable outcomes, and ROI.
• Strong strategic thinking with the ability to define AI roadmaps, priorities, budgets, and technology direction.
• Bachelor's degree in Computer Science, AI/ML, Data Science, Engineering, Mathematics, Statistics, or a related field; Master's/PhD preferred.
• Experience managing and mentoring cross-functional AI/ML teams is highly desirable.