Head of Artificial Intelligence

Company Overview

A prominent technology enterprise is rapidly advancing its AI transformation initiative, focusing on scalable AI technologies applicable to various business units. Investments span AI/ML, Generative AI, Agentic AI, optimization, digital twins, IoT, and conversational analytics.

Role Summary

This senior leadership position is responsible for establishing and expanding a high-functioning AI engineering team while actively contributing to technical strategy, architecture, and project execution.

Key Responsibilities

• Develop and implement an enterprise-wide AI capabilities and services roadmap aligned with organizational goals and measurable results.
• Create reusable AI platforms, services, frameworks, reference architectures, and engineering standards across AI/ML, Generative AI, and Agentic AI domains.
• Lead and nurture cross-functional teams including AI engineers, ML engineers, data scientists, and applied AI professionals.
• Design and scale enterprise-grade Generative AI and Agentic AI solutions that include features such as orchestration, retrieval-augmented generation (RAG), tool integration, memory management, evaluation, safety measures, and human oversight.
• Provide hands-on technical leadership covering model architecture, data pipelines, training processes, feature engineering, and AI/agent performance optimization.
• Oversee the production deployment of AI solutions ensuring they are scalable, reliable, secure, cost-effective, and maintainable.
• Implement AI operations practices including AI/MLOps, LLMOps, and AgentOps for deployment, monitoring, evaluation, incident handling, and continuous enhancement.
• Identify and prioritize AI business opportunities, including technology assessment, build-versus-buy analysis, and resource planning.
• Collaborate with technology, data, security, governance, and business teams to foster enterprise-wide AI adoption and execution.
• Establish responsible AI governance, risk management, and deployment standards to balance innovation with sustainable platform health.

Qualifications

• Proven extensive leadership in building and scaling enterprise AI platforms, capabilities, or products.
• Deep technical expertise across AI generations, including traditional machine learning, deep learning, Generative AI, large language models (LLMs), and Agentic AI.
• Experience in designing and launching production-level AI/ML and Generative AI systems at an enterprise scale.
• Strong knowledge of AI system architecture, MLOps/LLMOps/AgentOps, model evaluation, monitoring, governance, and ethical AI practices.
• Demonstrated success leading multidisciplinary teams comprising AI/ML engineers, data scientists, and applied AI experts.
• Capability to stay hands-on with technical guidance on architecture, modeling, data processes, engineering standards, and AI system performance.
• Strong commercial acumen with a proven record of converting AI initiatives into quantifiable business benefits.
• Excellent communication and stakeholder engagement skills, with the ability to influence senior leadership and manage complex organizational dynamics.
• Experience or knowledge in optimization, digital twins, IoT, or conversational AI is desirable.