AI Strategy & Enterprise Enablement Analyst

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Strategy & Enterprise Enablement Analyst based in United States. This role sits at the intersection of artificial intelligence, automation, business transformation, and enterprise governance.

You will turn prioritized business challenges into practical AI agents and automated workflows that improve productivity, accuracy, and scalability.

Working across functions such as Support, Sales, Operations, HR, Marketing, and Finance, you will identify opportunities and deliver measurable business value.

The position combines hands-on technical development with stakeholder engagement, enablement, and responsible AI practices.

You will work with enterprise systems, APIs, cloud platforms, data, and generative AI technologies while maintaining strong security and governance standards.

As a key contributor to the AI Center of Excellence, you will also help establish reusable solutions, documentation, controls, and operating practices.

This is an ideal opportunity for a technically capable AI builder who wants to play a meaningful role in scaling AI adoption across an organization.

Accountabilities

• Design, develop, test, deploy, and maintain AI agents and automated workflows addressing prioritized business use cases.
• Integrate AI solutions with enterprise systems such as CRM, ERP, and internal data sources using APIs, low-code platforms, and agent orchestration technologies.
• Develop reusable prompt libraries, agent configurations, technical components, and implementation patterns that can support broader organizational adoption.
• Evaluate AI platforms and tools in collaboration with IT, assessing technical capabilities, security, cost, integration requirements, and overall suitability.
• Monitor deployed solutions for accuracy, performance, model drift, cost, and failure conditions, taking ownership of remediation when issues arise.
• Maintain the technical operating foundation for AI initiatives, including repositories, environments, access controls, tools, licenses, and related infrastructure.
• Partner directly with business functions to analyze workflows, identify AI opportunities, define requirements, and determine where automation can improve efficiency, quality, and scalability.
• Lead pilots and phased AI rollouts by defining success criteria, testing approaches, implementation plans, and rollback conditions.
• Establish and report ROI metrics for AI initiatives, including baseline measurements and targeted improvements in manual effort or process cycle time.
• Support change management and adoption by working closely with process owners to ensure solutions are effectively integrated into day-to-day operations.
• Contribute to AI governance policies and documentation covering responsible use, privacy, cybersecurity, regulatory compliance, and risk management.
• Manage AI use-case intake and initial risk assessments for assigned business functions, applying established prioritization frameworks.
• Implement human-in-the-loop controls and other safeguards within AI solutions and clearly document how those controls operate.
• Maintain approved data classifications and ensure sensitive or regulated information is not introduced into unauthorized AI tools or systems.
• Participate in AI governance forums and communicate program progress, risks, and recommendations to executive stakeholders.
• Maintain key AI Center of Excellence assets, including use-case inventories, tool and model registers, governance decision logs, and production runbooks.
• Create documentation and cross-training materials that ensure continuity and allow responsibilities to be covered across the AI team.
• Develop AI adoption playbooks, prompting guidelines, training resources, and hands-on enablement sessions for internal teams.
• Advise stakeholders on practical AI applications, current technology capabilities, limitations, and responsible implementation approaches.

Requirements

• Bachelor’s degree in Data Science, Information Systems, Computer Science, Biomedical Engineering, Healthcare Informatics, Business Analytics, or a related discipline, or equivalent professional experience.
• 2–5 years of experience in software development, data analytics, automation, digital transformation, business process optimization, or a related field.
• Demonstrated profi…