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.

The Vice President, AI Platform leads product management for LPL’s enterprise AI Agent Platform, which enables teams across the firm to build, govern, deploy, monitor, and control AI agents at scale. This role owns the end-to-end platform strategy, defining how agents are developed, certified, operated, and retired within a secure, compliant, and production-ready environment. Partnering closely with engineering, security, risk, and business stakeholders, this leader ensures the platform delivers consistent controls, strong governance, and scalable capabilities that support advisor, operations, compliance, and corporate use cases.

Responsibilities:

• Define and execute the product vision, roadmap, and operating model for the AI Agent Platform, including lifecycle management from ideation through production and retirement

• Establish platform standards for agent identity, authentication, authorization, and governance, including scoped access, tool permissions, credential lifecycle, and enforcement controls

• Define and manage the system of record for agents, including registries for models, prompts, tools, ownership, versions, approvals, and production status

• Develop and enforce agent qualification and certification processes, including evaluation requirements, risk tiering, human-in-the-loop controls, and compliance reviews prior to deployment

• Define audit, logging, and recordkeeping requirements covering agent decisions, outputs, tool usage, user interactions, and approval workflows

• Establish and govern data protection standards, ensuring consistent classification and handling of sensitive, client, advisor, and firm data across all agents

• Implement controls for incident response, including capabilities to suspend, throttle, roll back, quarantine, or disable agents, along with defined escalation and resolution processes

• Own platform telemetry, monitoring, evaluation frameworks, drift detection, and alerting to measure agent performance, reliability, and business outcomes

• Define and manage cost controls, including usage tracking, rate limiting, budget attribution, and consumption reporting across agents, teams, and models

• Lead product input into build, buy, and partner decisions across platform components, including orchestration, gateways, evaluation, observability, registries, and tooling

• Partner with engineering, architecture, security, data, risk, compliance, and business teams to define requirements, data contracts, service levels, and adoption strategies

What are we looking for?

We are seeking a leader who is motivated to pursue greatness, consistently act with integrity, and is deeply driven to help our clients succeed This individual thrives in collaborative environments where teams win together, and contributes to a culture that encourages innovation and celebrates success to create and share joy

Requirements:

• 8+ years of product management experience, including ownership of platform, infrastructure, developer, data, AI, or enterprise technology products

• Experience building or scaling platforms used by multiple internal teams, business units, or product groups

• Experience with production AI, machine learning, automation, data, or agent-based systems, including areas such as identity, orchestration, evaluation, observability, or workflow automation

• Experience operating in regulated or enterprise environments where security, privacy, compliance, and audit requirements influence product delivery

• Strong technical understanding of APIs, cloud platforms, access controls, data systems, and production operations

Preferences:

• Ability to write clear product requirements and communicate technical decisions to business, risk, and executive stakeholders

• Bachelor’s degree in a related field or equivalent practical experience

• Experience with AI agent infrastructure, including agent identity, tool permissions, gateway enforcement, registries, evaluation frameworks, or audit trails

• Experience with responsible AI, model risk management, AI governance, or similar control frameworks

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