This role pays less than
82%
of similar roles. Most pay
$152,304–$235,750
— the shaded band above.
At the midpoint, this role pays about
$145k
versus about
$194k
for comparable roles.
Based on 240 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.
The AVP, AI Platform leads the shared AI platform and manages services that enable internal teams to register models, tools, and data while maintaining visibility into platform activity. This role is responsible for defining product strategy, roadmaps, and operational measures while managing registries for agents, prompts, and A2A workflows. The position involves overseeing runtime services like access controls, rate limiting, and PII handling, alongside monitoring for drift detection and adversarial testing. Key technical requirements include fluency in APIs, gateways, identity management, cloud architecture, and distributed systems. Candidates should have experience with LLM gateways, Kong, MCP, and model lifecycle management. The role operates within a regulated financial services environment, requiring the integration of audit records, compliance evidence, and FinOps data to ensure secure, scalable AI infrastructure for internal product teams.
Define and own the product strategy, roadmap, and operating measures for the shared AI platform.
Maintain registries for agents, tools, models, prompts, and workflows including versioning and status tracking.
Establish processes for the lifecycle of AI products, including registration, testing, certification, and retirement.
Manage runtime services such as access controls, policy enforcement, rate limiting, and PII handling.
Oversee production monitoring, drift detection, adversarial testing, and observability across all models and data.
Coordinate with engineering teams on incident management, failover procedures, and recovery testing.
Connect audit records and compliance evidence to the appropriate internal review teams.
Collect usage and cost data to support FinOps reporting, forecasting, and platform optimization.
What we're looking for
7+ years of product management experience including ownership of a shared platform, developer platform, infrastructure product, or enterprise technical capability.
Experience owning product strategy, delivery, adoption, and production performance.
Technical fluency in APIs, gateways, identity and authorization, cloud and data architecture, distributed systems, telemetry, and AI or machine-learning platforms.
Experience building services used by several product and engineering teams.
Experience working with engineering, Cybersecurity, Risk, Compliance, Privacy, Legal, data, Records Management, Supervision, and FinOps.
Strong communication skills to explain technical choices and production issues to senior leaders (preferred).
Experience with AI agents, LLM gateways, Kong, MCP, A2A, tool registries, model registries, prompt management, or policy engines (preferred).
Experience with AI evaluation, drift detection, red teaming, observability, or model lifecycle management (preferred); and experience in financial services or other regulated industries (preferred).