LPL Financial

Vice President

• Manage services help content
• Optimize the customer self-help knowledge base
• Transform the customer service experience
• Deliver knowledge-related activities, including project-related initiatives and migrations across platforms
• Lead new AI transformative initiatives and guide the knowledge management team
• Coach team members in new technologies

AVP, Knowledge Management

Artificial Intelligence

• Collaborating internally with our Product and Technology teams so they can get the most value out of Kong Platform
• Developing internal solutions & tools for the organization to help us push our technical boundaries and improve our ability to deliver AI integration to the organization
• Writing or editing technical documentation and knowledge base articles for the solutions you develop
• Maintain and upkeep Kong platform
• Configure and develop Kong plugins for authentication, rate limiting (including token-based throttling), logging, and transformation

Kong AI Gateway Engineer

Business Development Rep

• Responsible for recruiting high quality financial advisors to the LPL Financial Platform
• Establish and maintain a network of centers of influence (COI)
• Create and manage a recruiting pipeline to transition candidates (Financial Advisors) to LPL
• Evaluate advisor practices to ensure transferability of assets and adherence to corporate compliance and affiliation standards.
• Strong negotiation skills and the ability to compile and present competitive offerings in partnership
• Build and maintain strong internal and external relationships critical to success in the role.
• Maintain up-to-date status of your recruiting pipeline within Salesforce
• Develop and implement a strategy for engaging with existing recruits and for feeding / building the pipeline
• Meet monthly KPI’s required for the role – calls / meetings

AVP, Business Development

Product Manager

• Define product vision and roadmap for key advisor-facing AI capabilities.
• Translate advisor workflow friction into AI-powered solutions.
• Deliver production-grade AI capabilities with defined success metrics and adoption plans.
• Lead disciplined experimentation from hypothesis through pilot validation.
• Develop commercialization plans for successful pilots and manage phased rollout to enterprise adoption.
• Apply documented build-vs-buy-vs-rent frameworks.
• Conduct market, competitive, and capability assessments of potential vendor partners.
• Partner with Technology and Risk to integrate third-party AI solutions under enterprise guardrails.
• Ensure all AI products meet compliance, legal, risk and regulatory requirements before deployment.
• Own rollout strategy, training integration, and advisor enablement materials.

AVP, AI Product Manager

Full-stack Engineer

• Develop and maintain software products used by advisors and investors to support investment planning and client engagement.
• Perform peer-to-peer and team code reviews, promoting engineering best practices and sharing knowledge on emerging technologies.
• Collaborate with both technical and non-technical partners to support product delivery, system operations, and continuous improvement.
• Translate business requirements into technical solutions and actively contribute to sprint planning, backlog refinement, and demonstrations.
• Support Agile product development teams building cloud‑based, modern technology solutions.
• Work closely with Development, Architecture, QA, Release Management, and Support teams to design, develop, test, deploy, and maintain integrated platforms.
• Participate in Agile ceremonies and follow SAFe methodology, including daily scrums, sprint planning, and PI planning.

Senior Software Developer

Solutions Engineer

• Support end‑to‑end solution analysis for platform and integration initiatives, from discovery through delivery
• Analyze requirements and assist in defining target‑state architectures for cross‑platform solutions
• Create and maintain architecture artifacts such as system diagrams, integration flows, and technical documentation
• Assist with the design and analysis of API, integration, and gateway solutions that enable secure enterprise connectivity
• Partner with engineering and platform teams to ensure solutions align with established architecture standards and best practices
• Help identify risks, dependencies, and bottlenecks across architecture, security, and infrastructure
• Support platform modernization and migration efforts by analyzing current‑state solutions and documenting future‑state designs
• Contribute to clear communication of technical concepts, decisions, and trade‑offs to technical and non‑technical stakeholders

Solution Architect – Tech Foundations

• Design, implement, and maintain DLP controls across endpoints, email, SaaS, cloud platforms, APIs, and AI/ML data pipelines.
• Engineer DLP solutions that address AI-specific risks, including: Training-data leakage, Prompt and response data exposure, Model input/output inspection, Sensitive data misuse in AI experimentation and inference.
• Partner with AI engineering teams to embed security-by-design controls into AI platforms and workflows.
• Integrate DLP solutions with SIEM, CASB/CSPM, endpoint protection, cloud security, and AI observability platforms.
• Develop automation and scripting to support policy enforcement, exception handling, redaction, and data classification across dynamic environments.
• Evaluate emerging technologies for AI data protection, DSPM, and next-generation DLP capabilities.
• Tune DLP policies to minimize false positives while maintaining strong data-exfiltration and misuse controls—especially in AI-driven workflows.
• Assess existing DLP coverage and identify gaps across legacy systems, cloud platforms, AI tools, and third-party services.
• Stay current with emerging threats, AI security patterns, and regulatory developments, recommending updates to DLP and AI data-protection strategy.
• Partner with data owners, legal, privacy, compliance, AI teams, and business units to understand data flows and protection requirements.

AVP DLP Engineer

Backend Engineer

• Define and steward target‑state architecture for mission‑critical investor‑facing platforms, including upstream and downstream dependencies.
• Partner with business, product, and technology leaders to align architectural strategy with enterprise priorities and funding decisions.
• Guide and influence domain‑aligned solution and data architects to maintain architectural coherence and quality.
• Establish and evolve architectural standards, principles, reusable assets, and frameworks that drive scalability, security, performance, and quality.
• Lead modernization initiatives including cloud adoption, API‑first transformation, and migration from monolithic to microservices architectures.
• Identify opportunities for enterprise reuse, efficiency, and improved business outcomes through architectural alignment.
• Monitor emerging technologies (e.g., AI/ML, data mesh) and apply them thoughtfully to transform investor and advisor experiences.

Chief Architect, Investor Technology

Consultant

• Manage and triage incoming client feedback, ensuring timely acknowledgment, accurate routing, and closed-loop communication.
• Serve as a quality control checkpoint for consistent, professional client communications.
• Monitor timelines and service level expectations, flagging risks or delays and escalating issues as appropriate.
• Partner with feedback SMEs to support delivery of responses by tracking progress, sending reminders, and reinforcing expectations.
• Identify stale or aging feedback items and proactively re-engage stakeholders to move items forward.
• Participate in working sessions or support touchpoints with SMEs to address complex or sensitive feedback, escalating as needed.
• Maintain assigned SME coverage areas by supporting topic alignment and onboarding activities.
• Contribute to feedback reporting and governance activities by identifying issues, suggesting improvements, and following established workflows.
• Demonstrate and reinforce client-centric and hospitality-minded behaviors through daily actions and interactions.

Senior Consultant, Client Feedback

• Manage and triage incoming client feedback, ensuring timely acknowledgment, accurate routing, and closed-loop communication.
• Serve as a quality control checkpoint for consistent, professional client communications.
• Monitor feedback trends, escalating urgent or systemic issues as needed.
• Partner with cross‑functional feedback SMEs to drive delivery of responses within defined Service Level Agreements (SLAs) by tracking timelines, sending reminders, and proactively mitigating risks.
• Drive proactive oversight of feedback, including monitoring stale or aging items, and re-engaging stakeholders to move issues forward.
• Facilitate targeted touchpoints, support sessions, and working meetings with SMEs to address complex, sensitive, or high-risk feedback.
• Maintain SME coverage by managing topic alignment, identifying gaps, and supporting onboarding.
• Contribute to feedback governance through tooling enhancements, workflow improvements, and reporting that surfaces client sentiment and response effectiveness.
• Champion a culture of client-centricity, accountability, and continuous improvement across the organization.

AVP, Client Feedback

Analyst

• Support and collaborate with more experienced colleagues to deliver large-scale solutions
• Jointly participate in projects & tasks while advancing skills in discovery, design, and implementation of process improvements and automated workflows
• Optimize processes by conducting stakeholder interviews to compile needs assessment, identify requirements, and support solution design
• Conduct data validation and process testing exercises, identifying defects and proposing solutions or workarounds
• Work cross-functionality to deliver & implement more efficient workflows by combining backend data sources in Alteryx
• Research and resolve unknowns independently by leveraging resources and navigating the organization to obtain information and achieve objectives
• Drive continuous improvement by proposing ways to leverage data aggregation tools, automated workflows, or AI

Supervision Performance – Automation Analyst

• Analyze and monitor key performance indicators (KPIs) such as product adoption, deflection efficacy, and experiential feedback.
• Leverage descriptive analytics and data visualization to extract actionable insights to improve product performance.
• Leverage AI tools and innovative analytics to identify opportunities to improve knowledge content.
• Provide training and change management support to internal stakeholders and advisors for new launches and product enhancements.
• Participate in gathering and analysis of user feedback, usability testing and journey mapping.