AVP Agentic Platform Controls, Non-Human Identity & AI Security

LPL Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Fort Mill, NCCharlotte, NCAustin, TX
Salary
$108,665–$181,177 / yr
Posted
24 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k
This role $145k
$91k most similar roles pay here $278k

This role pays less than 88% of similar roles. Most pay $165,750–$241,500 — the shaded band above. At the midpoint, this role pays about $145k versus about $204k for comparable roles.

Based on 239 similar postings.

Employer

About LPL Financial

LPL Financial is the largest independent broker-dealer in the United States, providing brokerage and investment advisory services to independent financial advisors and financial institutions. Industry: Financial Services & Wealth Management

LPL Financial currently has 59 open roles on FindRole.

Listed pay typically runs $140,959–$234,882 across 54 roles with salary data.

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View all roles at LPL Financial

At a glance

TL;DR · AVP Agentic Platform Controls, Non-Human Identity & AI Security

AVP, Agentic Platform Controls, Non-Human Identity & AI Security leads the enterprise control plane for agentic technologies, non-human identities, and AI platforms. This role focuses on product strategy, governance, and operational controls to enable the secure adoption of autonomous systems and machine-operated technologies. The individual will build a foundational layer of identity, authorization, runtime controls, and risk management for teams developing agents, copilots, and multi-agent workflows. Key responsibilities include defining deployment standards, managing registries, and translating security requirements into platform capabilities. Required expertise includes technical fluency in APIs, cloud and data architecture, telemetry, and machine-to-machine authentication. The role addresses the challenge of securing emerging technologies like quantum computing and digital assets within a regulated environment. Essential skills include systems thinking, cross-functional leadership, and experience with model gateways, AI firewalls, and non-human identity governance.

What you'll do

  • Own the enterprise control framework for AI platforms, agentic systems, and non-human identities.
  • Define and operationalize audience-specific controls, access models, and deployment standards for enterprise AI.
  • Establish measurable controls for registration, approval, monitoring, auditability, and policy enforcement.
  • Lead assessment and governance of risks related to emerging technologies like quantum computing and autonomous systems.
  • Develop the product strategy and roadmap for registries, runtime enforcement, and data protection.
  • Translate security, regulatory, and operational requirements into specific platform capabilities and acceptance criteria.
  • Partner with engineering teams to manage identity, authorization, gateways, and API integration.
  • Track control coverage and performance metrics to communicate status and gaps to senior stakeholders.

What we're looking for

  • 7+ years of product management experience including ownership of a shared technical platform, security product, or enterprise capability.
  • Experience owning product strategy, roadmap, delivery, adoption, and production performance.
  • Technical fluency in APIs, cloud and data architecture, identity and authorization, telemetry, secure software delivery, and AI/ML systems.
  • Experience with identity and access management, non-human identity governance, machine-to-machine authentication, or enterprise platform security controls.
  • Experience translating security, risk, or policy requirements into specific product behavior and measurable tests.
  • Experience working with engineering, Cybersecurity, Risk, Compliance, Privacy, Legal, data, and business teams in a complex organization (preferred).
  • Strong written and verbal communication skills to explain technical decisions and control gaps to senior leaders (preferred).
  • Experience with AI agents, model gateways, non-human identity, or enterprise AI enablement platforms (preferred).

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