Distinguished Engineer, Trading

LPL Financial•Charlotte, NC

About The Position

LPL Financial is seeking an AI Distinguished Leader to define the vision, platforms, and responsible practices that bring AI-powered innovation to advisors, investors, and the teams that support them. The role combines financial-services technology expertise with the opportunity to modernize mission-critical platforms, create reusable enterprise capabilities, and turn emerging AI technologies into measurable business outcomes. As the AI Distinguished Leader - Trading & Wealth Technology, you will drive the adoption, governance, and scale of artificial intelligence across LPL's trading, advisory, and wealth management platforms. You will partner with business executives, product leaders, architects, data scientists, engineers, risk, and compliance stakeholders to identify high-value opportunities, accelerate intelligent automation, and modernize critical platforms. The role spans Generative AI, Large Language Models, Agentic AI, machine learning, intelligent decision systems, data platforms, and cloud-native architecture within a regulated financial environment.

Requirements

15 or more years of progressive technology leadership experience spanning software engineering, platform architecture, data engineering, AI/ML initiatives, and large-scale technology transformation.
10 or more years building and scaling engineering organizations.
Experience leading enterprise AI, digital transformation, or platform modernization initiatives within financial services, capital markets, wealth management, or FinTech.
Experience with trading systems, investment platforms, market data, wealth management technologies, and the regulatory considerations that shape those environments.
Experience across Generative AI, Large Language Models, Agentic AI, machine learning platforms, AI governance, data foundations, and cloud-native technologies.
Ability to translate complex business challenges into AI-powered solutions, align senior stakeholders, influence without direct authority, and communicate effectively with executive, board, and technical audiences.
Strong collaboration skills and the ability to deliver exceptional client experiences in fast-paced, team-oriented environments.
Integrity, a drive to help clients succeed, creativity, commitment to continuous improvement, and a collaborative approach.

Nice To Haves

Experience establishing or scaling an AI Center of Excellence or federated enterprise AI operating model.
Experience creating reusable AI platforms, APIs, intelligent workflows, or decision services adopted across multiple business domains.
Experience leading modernization of mission-critical, high-volume trading or investment platforms in a complex regulated organization.

Responsibilities

Define and execute the enterprise AI vision and roadmap for trading, advisory, and wealth management platforms, aligned to business priorities and measurable outcomes.
Identify and prioritize AI opportunities that improve advisor productivity, client experience, operational efficiency, risk management, and business growth.
Champion scalable adoption of Generative AI, Agentic AI, machine learning, and advanced analytics, including establishing AI Centers of Excellence, governance frameworks, and reusable best practices.
Lead modernization of trading and investment platforms through AI-enabled automation, intelligent workflows, cloud-native architectures, and modern practices for resiliency, scalability, performance, and observability.
Establish reusable AI platform capabilities, APIs, data products, and services that accelerate delivery across business domains.
Guide architecture decisions across buy, build, and partner strategies while protecting long-term platform sustainability.
Partner with data and architecture teams to establish enterprise data foundations and use large-scale structured and unstructured data to generate actionable insights and business value.
Drive responsible AI practices, including model governance, security, explainability, compliance, and risk controls appropriate for regulated financial services.
Establish metrics and KPIs that measure AI effectiveness, business impact, operational improvement, and return on investment.
Build trusted relationships across executive leadership, product management, architecture, engineering, data, compliance, risk, and business teams; influence strategic decisions across organizational boundaries without relying on direct authority.
Communicate complex AI, engineering, and architecture concepts to executive leaders, boards, and technical audiences, and serve as a trusted advisor on emerging technology trends, competitive dynamics, and innovation opportunities.