VP, AI Innovation & Enablement: Drive Enterprise AI

Lead with Purpose, Unlock Your Team’s Passion

At LPL, people leaders hold the key to the employee experience — shaping culture, driving performance, and guiding individuals to new heights. Because when that happens, we all win – clients, LPL, and most importantly our, employees.

If you’re ready to lead with intention and discover what’s possible, LPL Financial invites you to apply today.

Why This Role Matters

This VP, AI Innovation & Enablement leader will lead the organization responsible for identifying emerging AI technologies, developing reusable patterns, and enabling teams across the enterprise to adopt them effectively.

The team serves as the bridge between new AI capabilities and production implementation, ensuring the organization stays current with advances in generative AI and agent-based systems while maintaining strong engineering discipline.

This group works closely with the AI platform team, architecture, cybersecurity and AI solutions teams to translate experimentation into reusable patterns, reference architectures, and enterprise adoption.

Job Overview

• Maintain strong awareness of the rapidly evolving AI ecosystem

• Translate new AI capabilities into practical engineering patterns

• Accelerate adoption of the enterprise AI platform across engineering teams

• Ensure experimentation leads to reusable capabilities rather than isolated prototypes

• Provide a clear feedback loop to the AI Platform organization on emerging needs

Key Responsibilities

AI Capability Discovery

Continuously evaluate emerging AI technologies and techniques that can meaningfully improve enterprise AI systems, including:

• Large language models and reasoning models

• Agent frameworks and orchestration patterns

• Advanced retrieval architectures

• Multimodal AI systems

• Evaluation and benchmarking techniques

Applied Experimentation

Develop prototypes and reference implementations that validate new AI approaches, and produce reusable engineering patterns (not stand alone demos), including:

• Agent-based workflows

• Retrieval and knowledge access patterns

• Prompt engineering and reasoning workflows

• Tool-using AI systems

Reusable Asset Development

Translate experimentation into practical assets that accelerate the development of production AI systems across the organization:

• Reusable templates for AI applications

• Agent workflow frameworks

• RAG and knowledge integration patterns

• Small models/ synthetic data

Enterprise Enablement

Help engineering teams adopt AI capabilities effectively by:

• Advising teams designing AI-enabled systems

• Providing guidance on safe and reliable AI system design

• Running internal technical workshops and onboarding sessions

• Documenting best practices for AI application development

AI Adoption & Technical Evangelism

Drive awareness and adoption of AI capabilities across the enterprise, including:

• Demonstrating practical AI use cases and reference implementations

• Showcasing successful AI deployments internally

• Organizing engineering showcases, workshops, and hackathons

• Promoting consistent use of the enterprise AI platform

Demonstrations are expected to evolve into reusable patterns or production implementations.

What are we looking for?

We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness , act with integrity , and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

Requirements

• Minimum of 10 years experience in software engineering, machine learning engineering, or applied AI

• Experience designing or experimenting with modern AI systems (LLMs, RAG, or agent workflows)

• Experience with architecture thinking and ability to translate experimentation into practical engineering patterns

• Experience advising engineering teams or leading platform adoption initiatives

Core Competencies:

• Strong communication skills with the ability to engage both engineers and technical leadership

• Experience working in enterprise platforms or developer platforms

• Experience evaluating and delivering emerging technologies and…