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Role Descriptions: Position Summary

The Clinical Technologist AI Solutions Focus serves as the bridge between clinical business processes, technology solutions, and emerging Artificial Intelligence capabilities. This role partners with clinical operations, business stakeholders, vendors, and technology teams to identify opportunities where AI-driven solutions can improve efficiency, decision-making, data quality, and user experience across the clinical ecosystem.

The individual will maintain deep expertise in clinical technologies while acting as an AI champion, helping evaluate, implement, govern, and optimize AI-enabled tools and platforms that support clinical trial operations, data review, study execution, and business processes.

Key Responsibilities

Clinical Technology Leadership

Serve as a subject matter expert for clinical technology platforms and business processes.

Partner with stakeholders to understand clinical workflows, challenges, and technology needs.

Drive technology solutions that improve operational efficiency and data quality.

Support implementation, enhancement, and lifecycle management of clinical applications.

Collaborate with vendors and internal teams to ensure solutions align with business objectives.

AI Enablement and Innovation

Identify opportunities to leverage Artificial Intelligence, Generative AI, Machine Learning, and intelligent automation within clinical processes.

Evaluate emerging AI tools and technologies for potential business value and feasibility.

Partner with development teams to define AI use cases, requirements, and success criteria.

Assist in the design, testing, validation, and deployment of AI-enabled solutions.

Promote responsible AI adoption in accordance with company governance, security, privacy, and compliance standards.

Develop business cases demonstrating the value and impact of AI-driven capabilities.

Product and Solution Management

Translate business requirements into technical specifications and user stories.

Participate in roadmap planning for AI-enabled clinical products and services.

Monitor solution performance and identify enhancement opportunities.

Support user acceptance testing, validation activities, and release management.

Change Management & Adoption

Act as an AI advocate and trusted advisor for business stakeholders.

Provide guidance, training, and best practices for AI solution adoption.

Create documentation, user guides, and educational materials.

Measure adoption metrics and business outcomes to drive continuous improvement.

Data & Analytics

Collaborate with data engineering and analytics teams to ensure data readiness for AI initiatives.

Support data quality, data governance, and information management practices.

Leverage analytics and insights to identify trends, risks, and optimization opportunities.

Required Qualifications

Bachelors degree in Information Technology, Computer Science, Health Informatics, Life Sciences, Engineering, or a related field.

Experience supporting clinical, healthcare, life sciences, or regulated technology environments.

Strong understanding of clinical business processes and technology solutions.

Experience gathering requirements and partnering with business stakeholders.

Excellent analytical, communication, and problem-solving skills.

Demonstrated ability to lead cross-functional initiatives.

Preferred Qualifications

Experience with Artificial Intelligence, Generative AI, Machine Learning, or intelligent automation technologies.

Familiarity with Large Language Models (LLMs) such as Microsoft Copilot, Azure OpenAI, Claude, ChatGPT, or similar platforms.

Understanding of AI governance, responsible AI principles, privacy, security, and compliance considerations.

Knowledge of clinical trial systems, clinical data management, or life sciences technology ecosystems.

Experience with cloud platforms such as Azure or AWS.

Experience developing AI use cases, proof-of-concepts, or innovation initiatives.

Key Success Measures

Successful identification and implementation of AI-driven business improvements.

Increased efficiency and productivity within clinical processes.

Adoption and effective utilization of AI-enabled tools.

Positive stakeholder engagement and user satisfaction.

Delivery of scalable, compliant, and secure technology solutions.

Contribution to innovation and digital transformation objectives.