Overland Park, Kansas, United States of America / Philadelphia, Pennsylvania, United States of America
Type
Full Time
Responsibilities:
Strategic Development and Implementation: Develop and execute strategies for AI technologies and solutions across Clarivate
AI Expertise: Utilize deep understanding of AI technologies, algorithms, and frameworks to deliver and broker effective AI services across the segments and for internal operations
Collaboration and Stakeholder Engagement: Work closely with cross-functional teams and business partners to identify opportunities and assist with strategies for AI application and implementation
Architectural Design: Create and maintain robust AI architecture using leading technology frameworks, ensuring adaptability, efficiencies, and cost effectiveness now and in the future
Regulatory Compliance: Build and scale governing standards, cost optimization, platform optimization, and audit trails for generative AI architecture
Governance: Lead the AI governance committee overseeing the ethical and responsible development, deployment, and use of artificial intelligence within an organization through a framework of policies, standards, and guidelines that govern the use of AI, ensuring that AI applications align with legal regulations and ethical norms.
Requirements & Skills:
Bachelor’s or master’s degree in Computer Science, Information Systems, Engineering, Machine Learning, or related fields
Minimum 10 years of AI Architecture, AI Engineering, Technology Strategy, or similar disciplines, with a focus on collaboration within large-scale engineering teams to design cost-effective technology solutions
Minimum 10 years of experience working with enterprise customers, providing engineering, infrastructure, and technical guidance
Minimum 10 years in a technical role delivering projects in Data Analytics, Machine Learning, Cloud Computing Platforms, and Service-oriented architecture, with a preference for Large Language Model (LLM) technology
Exceptional communication skills to articulate complex AI concepts to non-technical audiences and deliver compelling presentations to large groups
Experience in establishing and leading enterprise-wide AI Governance body
Proficiency in Programming Languages: Demonstrated proficiency in programming languages commonly used in AI and machine learning, such as Python, R, or Java
AI Frameworks and Libraries: Experience with popular AI frameworks and libraries, including TensorFlow, PyTorch, scikit-learn, Keras, or Apache MXNet
Machine Learning Techniques: In-depth understanding of various machine learning techniques, including supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing
Cloud Computing Platforms: Familiarity with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) for AI development, deployment, and scaling
Big Data Technologies: Experience with big data technologies and tools such as Apache Spark, Hadoop, Apache Cassandra, and distributed computing frameworks for handling large-scale datasets
Data Engineering: Knowledge of data engineering principles and best practices for data acquisition, transformation, storage, and retrieval in AI applications
AI Governance and Compliance: Understanding of regulatory requirements, industry standards, and best practices related to AI governance, ethics, privacy, and security
Software Development Lifecycle: Experience with the software development lifecycle (SDLC) and agile methodologies for managing AI projects from inception to deployment
Quantitative Analysis Skills: Strong quantitative analysis skills and the ability to analyze complex datasets, identify patterns, and derive actionable insights to inform decision-making
Continuous Learning and Innovation: Demonstrated commitment to continuous learning and staying updated on the latest advancements in AI technologies, techniques, and methodologies
