VP, Product & Technology AI Solutions Product Manager

LPL Financial•Fort Mill, SC

1d•$135,960 - $226,600•Hybrid

About The Position

The Vice President, Product and Tech AI Solutions Product Manager will lead the modernization of LPL’s Product Development Lifecycle (PDLC) and Software Development Lifecycle (SDLC) through practical AI-enabled workflows with humans in control. Reporting to the Senior Vice President of AI Business Solutions, this product leader will deliver a clear roadmap and adoption plan across product management, engineering, DevOps, architecture, quality engineering, security, and governance. The role focuses on accelerating value velocity by empowering product managers, reducing late-cycle churn, shortening review queues, improving developer experience, and increasing release stability. This leader will partner closely with the Technology teams that build and operate platforms and tools and will be accountable for measurable improvements in cycle time, rework, review turnaround time, production stability, and incident prevention.

Requirements

Proven ability to define product vision, build roadmaps, prioritize backlogs, and drive adoption for internal products and workflows.
Deep understanding of PDLC and SDLC failure modes in real organizations, including how unclear intent, slow reviews, and weak artifacts create churn.
Ability to prioritize improvements that reduce toil, improve release confidence, and prevent recurring incidents.
Experience introducing AI drafting and analysis while maintaining human ownership, review, and auditability.
Comfort establishing baselines, running pilots with clear criteria, and measuring impact across speed, quality, and stability.
Ability to work effectively with engineering on integration patterns, access controls, observability, and automation without acting as the engineering owner.
Ability to work with security, compliance, and risk teams in a regulated environment and improve review speed through better inputs and clearer evidence.
Track record driving adoption across teams through training, communications, and continuous feedback.
Clear communication that surfaces tradeoffs, progress, risks, and decisions.
Bachelor’s degree in Business, Engineering, Computer Science, Information Systems, or a related field.
8 or more years of experience in product management, engineering, delivery, or adjacent roles, with a track record improving delivery outcomes in complex organizations.
5 or more years leading cross-functional initiatives that changed how teams build and ship software.
Experience introducing workflow tooling or standards that reduced cycle time, reduced rework, improved release confidence, or improved reliability.
Proven experience operating in regulated environments with security, compliance, and audit expectations.

Nice To Haves

Advanced degree is a plus.
Financial services experience, especially in highly regulated technology and operations environments.
Experience with developer productivity tooling, DevOps practices, quality engineering, and release management.
Experience applying AI to delivery workflows, including requirements drafting, code understanding, test drafting, release documentation, or incident learning.
Experience partnering with platform engineering, SRE, and enterprise architecture teams.

Responsibilities

Own a roadmap that improves speed, quality, and predictability across discovery, build, test, release, and learning.
Translate priorities into sequenced pilots, lightweight standards, and tooling requirements that engineering teams can implement and run.
Introduce AI where it removes drafting and synthesis work, then require human review and edits before outputs become decisions or artifacts.
Standardize a small set of lightweight artifacts and quality checks that reduce late-cycle churn.
Focus on common causes of rework: unclear problem statements, missing edge cases, missing data handling constraints, and acceptance criteria that cannot be tested.
Partner with architecture, security, and compliance teams to reduce time spent in review queues.
Improve review speed by tightening inputs, capturing context up front, and using consistent templates.
Partner with DevOps and platform teams to reduce friction in the build and release process.
Focus on faster local setup, fewer manual steps to ensure safe shipping, clearer service ownership, and documentation engineers can trust during an outage.
Improve how teams prepare releases so work is not left to the end.
Align with DevOps, QE, and governance partners on what must be true before a release is approved, and ensure teams can produce that evidence as they build.
Improve code and system understanding by keeping service documentation current and tied to repositories and runtime behavior.
Partner with Technology and Business Reporting and Analytics to establish baselines and targets for lead time, cycle time, review turnaround, defect escape, change failure rate, production incident rate, mean time to restore, rework, and onboarding time.
Run fast-cycle pilots that show results within weeks.
Define success criteria up front, publish results, scale successful patterns through engineering partners, and shut down pilots that add work without improving delivery.
Define requirements for tooling based on workflow needs, auditability, access controls, and integration with existing platforms.
Partner with procurement and risk teams to evaluate vendors and prevent shadow tooling or data handling issues.
Establish a regular cadence with product, engineering, DevOps, security, compliance, and risk leaders to surface what is slowing delivery, make decisions, and track adoption.