VPII, Software Engineering Manager & AI Lead - M&A & Partner Integration

LPL Financial LLC; San Diego (CA); On-site; USD 211,356 - 352,260; Full time

Job summary

LPL Financial is seeking a hands-on AI engineering leader to own the Tenant Engine, a critical AI-driven static-analysis and remediation framework supporting multi-tenant migrations. You will guide the team, own the roadmap, and optimize remediation quality, throughput, and cost at portfolio scale.

The role requires deep experience with production LLM/GenAI systems, a strong engineering background, and leadership across distributed teams.

Qualifications

• 10+ years of progressive software, AI, ML, platform, or data-intensive engineering experience.
• 5+ years in AI/ML or platform technical leadership.
• 3+ years leading engineering teams.

Responsibilities

• Own the Tenant Engine roadmap and operating rhythm.
• Direct regeneration cycles: scan → noise-filter → LLM-validation → remediated-code generation.
• Govern noise-filter rules and prompts; balance false positives and risk.
• Lead and develop the Applied AI Engineer and related team members.
• Oversee scan operations at scale across 900+ repositories.

Skills

AI/ML leadership

Production LLM/GenAI ownership

Roadmap and delivery at scale

Education

Bachelor’s degree in Computer Science or related field

Tools

Bedrock

AWS EKS

S3

Job description

Overview

Lead with Purpose, unlock your team’s passion. LPL Financial seeks a hands-on AI engineering leader to own the Tenant Engine, a critical AI-powered static-analysis and remediation framework supporting a high-visibility, portfolio-scale multi-tenant migration. This role combines technical depth in LLM/GenAI systems, disciplined engineering execution, and people leadership to improve code remediation quality, scan throughput, and operating cost at scale.

Responsibilities

• Own the Tenant Engine roadmap and operating rhythm: prioritize remediation automation, portfolio-scale scanning, and the SME-gated regeneration loop to sustain migration progress.
• Direct regeneration cycles: lead each scan → noise-filter → LLM-validation → remediated-code generation cycle, incorporating SME feedback and maintaining measurable progress through the Discovery loop.
• Govern noise-filter rules and prompts: review and approve NF rule changes and validator/sampler prompt iterations, balancing false positives, must-fix coverage, and migration risk.
• Lead and develop the team: supervise the Applied AI Engineer, AI Platform Engineer, and scan-operations analysts; set goals, remove blockers, and run the weekly engine standup.
• Oversee scan operations at scale: ensure scan coverage, SLA performance, output integrity, and per-finding cost across ~900+ repositories in partnership with platform engineering.
• Coordinate cross-track handoffs: partner with DB & App and E2E QE leads to move remediated findings into migration execution and represent the engine in Architecture Review Board decisions related to G-category RLS/batch work.
• Report quality and economics: translate false-positive rate, actionability, throughput, and unit-cost trends for senior leadership and governance forums.
• Build operational independence: establish runbooks and processes so the engine can operate, improve, and scale without executive intervention.

What are we looking for?

We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and help clients succeed. We value creativity, continuous improvement, and a culture of winning together and sharing joy in work.

Requirements

• AI/ML and engineering leadership: 10+ years of progressive software, AI, ML, platform, or data-intensive engineering experience, including 5+ years in AI/ML or platform technical leadership and 3+ years leading engineering teams.
• Production LLM/GenAI ownership: Experience owning production LLM/GenAI systems, including prompt and evaluation pipelines, LLM validation at scale, and output quality/cost gating on AWS Bedrock or equivalent.
• Roadmap and delivery at scale: Experience owning a technical roadmap and delivering across teams in large-scale or regulated programs, including portfolio-scale systems with hard deadlines.
• Static analysis and automated remediation: Experience leading large-scale code analysis, automated remediation, developer tooling, or similar engineering productivity programs with the depth to review code, prompts, and architecture decisions.

Education

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience; Master’s degree preferred.

Core Competencies

• Hands-on technical leadership: credibility through sound technical judgment while developing the team to operate with increasing independence.
• Systems thinking and prioritization: optimize the full scanning, validation, remediation, and handoff pipeline while focusing SME and engineering capacity on must-fix work.
• Decisive executive communication: make evidence-based decisions on NF rules and prompts, and clearly communicate quality, cost, throughput, and risk to senior stakeholders.

Preferences

• Experience operationalizing AI in regulated financial-services or other compliance-driven environments.
• Familiarity with AWS-native ML/data infrastructure (Bedrock, EKS, Neptune, S3, Step Functions) and infrastructure-as-code practices.
• Background in multi-tenancy, platform consolidation, or large-scale application modernization programs.

Pay Range

$211,356.00 - $352,260.00

Actual base salary varies based on factors including relevant skill, experience, education, internal benchmarks, performance, and location. LPL Total Rewards package is competitive, including 401K matching, health benefits, stock options, PTO, volunteer time off, and more.

About LPL

LPL Financial Holdings Inc. (Nasdaq: LPLA) is a leading wealth management firm serving over 32,000 financial advisors and approximately 8 million clients. For more information, visit www.lpl.com.

Note: EOE. This description includes information on interviews and contact procedures consistent with standard practice; LPL will communicate from an @lplfinancial.com email address. If you have questions about the application process, contact LPL’s HR Solutions Center at [phone].