Distinguished Architect, Artificial Intelligence

LPL Financial•Charlotte, TX

About The Position

Why Should You Join the Enterprise Architecture Team at LPL Financial? At LPL Financial, our Architecture Team sits at the very center of strategy and transformation. We partner across business, product, and technology to design the blueprints that shape the future of wealth management. By setting standards, frameworks, and patterns, we enable the enterprise to innovate with speed while ensuring resilience, scalability, and regulatory compliance. As LPL expands its investment in Artificial Intelligence, the Architecture Team plays a pivotal role in defining how AI/ML, agentic AI, and advanced analytics are responsibly and effectively adopted. From giving advisors smarter insights, to automating compliance, to delivering more personalized investor experiences, AI is central to how we redefine wealth management. Joining the Architecture Team today means influencing enterprise-wide decisions, building sustainable frameworks for innovation, and seeing your work directly impact millions of clients and advisors. Here, architecture is not just about technology design — it’s about shaping the future of financial advice. Job Overview The Distinguished Architect, Artificial Intelligence, is a senior thought leader and individual contributor who drives the vision, design, and governance of AI solutions across LPL. Reporting to the Head Of Architecture, this role will: Establish LPL’s enterprise AI strategy and roadmap, including adoption of agentic AI to augment advisor workflows, automate servicing, and enable proactive client engagement. Define and govern architecture principles for AI adoption — spanning data platforms, ML pipelines, generative AI, and multi-agent systems. Serve as a core member of the AI Governance Council, shaping enterprise-wide standards for responsible, ethical, and compliant AI adoption. Partner closely with product, engineering, and data leaders to identify and scale the highest-value AI use cases in wealth management. Act as a trusted advisor to senior executives on AI opportunities, risks, ethics, and implementation trade-offs.

Requirements

15+ years in enterprise technology and architecture, with 7+ years in AI/ML/advanced analytics.
Experience participating in or leading AI governance councils, model risk committees, or equivalent regulatory forums.
Proven expertise with AI agent frameworks (LangChain, AutoGen, CrewAI, or equivalent) and multi-agent system design.
Strong track record designing AI/ML systems in regulated industries (financial services strongly preferred).
Strong understanding of wealth management, trading, or securities domains, with ability to link AI to advisor and investor value.
Graduate degree in Computer Science, AI, Data Science, or related field preferred.
Expertise in agentic AI systems, including reasoning, planning, and autonomous task execution.
Proficiency with AI/ML ecosystems (Python, PyTorch, TensorFlow, Hugging Face, LangChain, AutoGen, AWS Bedrock, Azure AI).
Strong grounding in AI/ML and agent governance — model lifecycle management, explainability, auditability, and risk controls.
Familiarity with financial services regulations impacting AI/ML, including SEC, FINRA, and data privacy laws.
Experience with MLOps/AgentOps, continuous learning pipelines, and real-time AI decisioning frameworks.

Nice To Haves

Financial services experience, especially in wealth management, advisory, or trading.
Demonstrated thought leadership in responsible AI or agentic AI (publications, regulatory engagement, industry consortiums).
AWS/Azure cloud certifications with AI/ML specialization.

Responsibilities

Define and Govern AI/ML/Agentic AI Architecture: Develop enterprise AI reference architectures, patterns, and guardrails — including multi-agent orchestration, reasoning frameworks, and AI safety controls.
AI Governance Council Leadership: Contribute to the design and enforcement of LPL’s AI governance framework through active participation in the AI Governance Council, ensuring consistency with the Architecture Review Board (ARB) and Data Design Authority (DDA).
Identify High-Value Use Cases: Partner with business and product leaders to prioritize AI opportunities such as advisor copilots, agent-based onboarding, autonomous compliance monitoring, and personalized financial insights.
Enable Responsible AI: Drive enterprise adoption of explainability, bias monitoring, risk assessment, and regulatory compliance frameworks for both predictive models and autonomous agents.
Partner and Influence: Collaborate across domains — including data, infrastructure, application, and security architecture — to enable secure, scalable deployment of AI and agentic systems.
Blueprint and Standards Leadership: Ensure AI/agentic AI solutions are represented in enterprise blueprints and align with LPL’s modernization strategy.
Thought Leadership: Evangelize LPL’s AI strategy internally and externally, representing the firm in regulatory, industry, and client-facing forums.