AI Transformation & Enablement Analyst

Position Summary

We are seeking an AI Transformation & Enablement Analyst to report directly to the AI Strategy Leader and drive our company’s strategy and execution around artificial intelligence. This role sits at the intersection of AI strategy, operational transformation and product innovation.

Key Responsibilities

• Evaluate, select, and rollout of AI-driven tools to enhance productivity, ensuring adoption and measurable impact.
• Partner with Loftware leaders for measurement and continuous performance metric tracking of the effectiveness and ROI of all AI initiatives.
• Go-to-market and customer success operations core responsibilities include: AI-assisted sales workflows, AI-driven customer success insights, AI-powered support operations, field enablement, AI messaging support.
• Collaborate with product management to plan, design, and implement AI-powered product features, from concept to delivery.
• Work with enterprise architects to ensure consistent use of approved models, frameworks, and AI platforms across products and teams.
• Partner with the CISO and AI Innovation Committee to ensure all AI initiatives protect data integrity, intellectual property, and comply with security and privacy standards.
• Stay current on AI trends, tools, and practices, guiding the organization on emerging opportunities and risks.

Qualifications

• Experience working with AI/ML technologies, generative AI platforms, or LLM-powered applications in a SaaS or enterprise software environment.
• Proven track record of implementing AI-driven tools internally or launching AI-powered product capabilities.
• Strong understanding of LLMs, ML frameworks, cloud AI services (AWS, Azure), and their practical application in enterprise and product contexts.
• Experience working cross-functionally with product management, engineering operations and security.
• Excellent program management, communication, and stakeholder alignment skills.

Preferred Qualifications

• Experience rolling out productivity tools and measuring their adoption and impact.
• Knowledge of MLOps and AI deployment practices at scale.
• Familiarity with compliance and risk considerations for AI (e.g., data residency, model governance).
• Hands-on technical expertise to guide proof-of-concepts and vendor evaluations.