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Lead the strategy, architecture, development, and delivery of scalable AI/ML and GenAI solutions. Provide technical and people leadership to AI/ML engineering teams, fostering engineering excellence and talent development. Oversee production AI/ML systems, including ML, Deep Learning, NLP, GenAI, and LLMs. Drive engineering best practices across MLOps, DevOps, automation, monitoring, reliability, and continuous improvement. Partner with stakeholders to translate complex business needs into scalable AI solutions, establishing appropriate evaluation criteria, monitoring, and lifecycle controls.

Ensure AI solutions meet high standards for reliability, quality, fairness, accountability, transparency, privacy, and security. Mentor and develop engineering talent, accelerating AI adoption and innovation. Provide leadership and accountability for the performance of managers and senior professional staff. Your impact will be at the operational, business unit, or market level, aligning with company policies and flexible work arrangements.

A Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or equivalent experience is required. Significant experience leading AI/ML engineering and delivering production-scale AI solutions is essential. Proven ability to build and scale AI/ML systems with a production-focused engineering approach is necessary. Strong knowledge of cloud platforms, model deployment, monitoring, and AI engineering practices is expected.

Deep understanding of Machine Learning, Deep Learning, NLP, Generative AI, and LLMs is crucial. Demonstrated technical leadership, people leadership, stakeholder management, and cross-functional delivery skills are a must. The ability to define AI success criteria and guide teams through experimentation, evaluation, production deployment, and continuous improvement is also key.