AI Director

Responsibilities

AI Model Development & Deployment : Lead design, development, and deployment of ML models, LLMs, and RAG systems with robust pipelines

Technology Leadership : Monitor emerging AI technologies, conduct strategic assessments, and drive adoption of cutting-edge AI frameworks and methodologies

Business Engagement : Collaborate with business units to identify AI use cases, translate requirements into technical solutions, and present strategic recommendations to executive leadership

Team Leadership : Build, lead, and mentor teams of data scientists and ML engineers while fostering innovation and continuous learning

AI Governance : Enforce AI governance frameworks, ethical guidelines, and organization-wide AI literacy initiatives

Strategic Planning : Develop AI roadmaps, manage project budgets, and coordinate cross-functional initiatives to drive business transformation

Innovation Management : Lead proof-of-concept initiatives, establish academic partnerships, and ensure scalable AI infrastructure for production applications

Job Requirements

Education & Experience : Bachelor's degree in Computer Science / Data Science / ML or relevant fields (Master's preferred) with 7-10 years progressive AI / ML experience including 3-5 years in leadership roles

Technical Expertise : Deep expertise in ML algorithms, LLMs, RAG architectures, and production deployment using frameworks and cloud services (GCP stack preferred)

Programming & Data : Expert Python programming, strong SQL skills, experience with big data technologies (Spark, Kafka) and cloud AI platforms

Leadership Experience : Proven track record building and scaling technical teams, managing P&L responsibility, and translating business requirements into AI solutions

Business Acumen : Strong presentation skills to communicate complex technical concepts to stakeholders, experience with AI governance and regulatory compliance

Industry Knowledge : Understanding of AI ethics, bias mitigation, responsible AI practices, and enterprise AI security best practices

Preferred Qualifications : Cloud certifications, active conference and event participation and track record of successful AI product launches

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