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Infinitice specializes in IT staff augmentation, connecting businesses with highly skilled professionals across data, analytics, and technology roles. We help organizations scale quickly with the right talent at the right time.

Our client is seeking to add an AI Specialist to their team for a short-term project. Below are the requirements. Please review and apply if you are a fit.

Telecommuting is not allowed in this position.

The AI Specialist will lead the design, development, and launch of an enterprise AI innovation program. This role focuses on assessing organizational readiness, strengthening innovation culture, defining operating models, and establishing success metrics that align AI initiatives with business priorities and existing technology standards.

The ideal candidate will combine hands-on AI knowledge with strong collaboration, change management, and program leadership skills. This position is innovation and cultural change management first, with close partnership across teams responsible for implementing AI solutions.

Responsibilities

• Lead the development and launch of an AI innovation program, including governance, operating models, success metrics, and adoption frameworks.
  
• Assess organizational readiness, innovation culture, and business needs to identify opportunities for AI-enabled transformation.
  
• Collaborate with cross-functional stakeholders to identify high-value AI use cases, gather requirements, and prioritize initiatives based on business impact.
  
• Design, develop, validate, and support the deployment of AI models, applications, and solutions that improve business processes and decision-making.
  
• Partner with data, technology, and business teams to prepare data, select appropriate models, and ensure solutions align with enterprise standards.
  
• Create roadmaps that sequence AI initiatives, balance feasibility and impact, and support sustainable adoption across the organization.
  
• Promote knowledge sharing, stakeholder engagement, and cross-functional collaboration to build AI awareness and capability.
  
• Monitor emerging AI technologies, research, industry trends, and best practices to keep the organization at the forefront of innovation.
  
• Measure outcomes and communicate progress, risks, learnings, and business value to leadership and stakeholders.
  

Requirements

• Strong understanding of artificial intelligence, machine learning, data science, and analytics concepts.
  
• Experience identifying, evaluating, and prioritizing AI use cases in a business or enterprise environment.
  
• Ability to translate business needs into technical requirements and communicate technical concepts to non-technical audiences.
  
• Experience supporting AI model development lifecycle activities, including data preparation, model selection, training, validation, deployment, and performance monitoring.
  
• Demonstrated ability to lead change management, innovation programs, stakeholder engagement, or enterprise adoption initiatives.
  
• Strong collaboration skills with the ability to work across business, data, technology, and leadership teams.
  
• Excellent communication, facilitation, analytical thinking, and problem-solving skills.
  

• Experience building or supporting AI innovation programs, centers of excellence, digital transformation initiatives, or emerging technology programs.
  
• Familiarity with responsible AI, AI governance, model risk considerations, data privacy, and ethical AI practices.
  
• Experience with cloud-based AI and machine learning platforms.
  
• Exposure to data visualization, reporting, and executive-level storytelling.
  
• Experience working in complex, cross-functional, or matrixed organizations.
  

Experience Level

Mid-Senior level. Candidates should have demonstrated experience applying AI, machine learning, analytics, innovation strategy, or technology adoption practices in a professional setting.

Technical Environment

Python, R, TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Databricks, Jupyter Notebooks, AWS SageMaker, AWS EC2, AWS S3, Azure Machine Learning Studio, Azure Databricks, SQL, NoSQL databases, Tableau, and Power BI.