VPII, Agentic AI/ML Engineering Leader

LPL Financial Services•Austin, TX

64d

About The Position

LPL Financial is committed to empowering advisors and their clients with technology that delivers efficiency, insight, and growth. We are seeking a proven leader to serve as VPII, AI/ML Engineering, responsible for accelerating LPL's ability to unlock business value through artificial intelligence and machine learning. This role will lead the design, build, and scaling of our AI/ML platform and reusable AI capabilities, while also overseeing solution delivery teams that transform these capabilities into client- and advisor-facing value. The ideal candidate will have a track record of rapidly delivering AI/ML-driven business outcomes at scale, demonstrating measurable P&L impact, and driving transformation in regulated industries.

Requirements

Proven success leading large-scale AI/ML engineering initiatives that delivered measurable business value in regulated industries.
Demonstrated ability to deliver rapid execution and scaling of AI/ML platforms, including reusable asset libraries.
Deep expertise in modern tech stacks (AWS, Snowflake, LangGraph, LangChain, Bedrock) and MLOps frameworks.
Strong knowledge of data management, information security, and financial data product strategies.
Track record of driving P&L impact and clearly articulated ROI from AI/ML initiatives.
Exceptional communication skills, with the ability to influence both technical and business leaders.
Advanced degree in Computer Science, Engineering, Data Science, or related field preferred.

Nice To Haves

Experience in financial services or wealth management, with understanding of compliance, security, and client trust.
Ability to balance engineering excellence and innovation with regulatory requirements.
Visionary leadership paired with urgency in technical execution.

Responsibilities

Define and deliver LPL's AI/ML enterprise engineering strategy, ensuring alignment with advisor, client, and enterprise needs.
Partner with LPL business leaders to identify, articulate and prioritize AI/ML initiatives that enhance client experience, operational efficiency, and competitive differentiation.
Act as a champion for AI adoption, articulating ROI and business impact at the executive level.
Drive and build our our high-performing AI and ML Engineering team, focusing efforts on continuous learning and delivery of the latest AI technologies tied to business growth, operational efficiency and reduction in cost to serve.
Foster a culture of collaboration, accountability, speed, and innovation while establishing and maintaining strong engineering standards and governance.
Deliver AI/ML solutions that create measurable improvements in data value, partnering with upstream data technology teams to organize and provide feedback on data product development and use.
Lead the development and scaling of LPL's AI/ML foundational platforms, expanding the use of AWS SageMaker and Bedrock capabilities while exploring multi-cloud/hybrid options based on demand/need. Experience in multi-cloud environments preferred.
Integrate Knowledge Graphs to enhance semantic understanding, contextual reasoning, and relationship mapping across enterprise data assets.
Implement and optimize Vector Stores to support GenAI Retrieval-Augmented Generation (RAG) architectures, enabling scalable and performant semantic search and document retrieval.
Explore and deploy Multi-Agent Orchestrationframeworks to coordinate specialized AI agents for complex task execution and dynamic decision-making.
Expand MLOps and ML platform capabilities to ensure compliant, scalable delivery of AI tooling and model management automation, learning and governance in partnership with infosec and compliance teams.
Deliver Agentic Framework and AI Agents to deliver intelligent, automated workflows that directly impact advisor productivity and client outcomes.
Establish a library of reusable AI assets/capabilities that can be applied across business lines to accelerate innovation, including OpenAI/GPT orsimilar APIs, Hugging face model hub or prebuilt models for common tasks such as parsing and summarizing data assets; reducing time to value and duplication.
Partner across Data Technology to access and further develop strategy to expedite delivery of scalable reliable data storage, querying, preparation and ability to handle large data volumes and future storage for model reuse.
Collaborate with the Chief Data & AI Officer (CDAO) function to influence product roadmaps and empower product owners to embed AI features into 2026 and 2027 product plans.
Ensure alignment with LPL's data management, information security, and data product strategies.
Build AI features and solutions that meet or exceed regulatory and compliance standards critical to financial services.
Establish frameworks for ethical, transparent, and responsible AI adoption.