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About the Role

LPL Financial is seeking a highly technical and hands-on AI engineering leader to design, build, and deploy next-generation AI solutions for advisors and business partners. This individual contributor role focuses on developing production-grade AI/ML capabilities while collaborating with various teams. The ideal candidate will combine deep technical expertise in AI/ML and Generative AI with the ability to influence architecture, mentor engineers, and drive AI solution adoption across the enterprise. This position offers the opportunity to shape LPL's AI platform strategy, build advisor-facing AI capabilities, and establish engineering best practices for scalable, secure, and responsible AI. Over time, this role may provide leadership opportunities for a small team of AI engineers.

Responsibilities

Design, develop, and deploy production-grade AI/ML solutions that support LPL Financial's business objectives and advisor experience.
Architect and build AI-powered applications using modern technologies such as LLMs, generative AI, agentic workflows, RAG architectures, and machine learning models.
Lead the end-to-end software engineering lifecycle for AI solutions, including design, development, testing, deployment, monitoring, and optimization.
Partner with Wealth Management, Operations, Risk, Marketing, Product, and Engineering teams to identify high-value AI use cases and translate business requirements into scalable technical solutions.
Develop and deliver AI-enabled products, platforms, and tools that improve advisor productivity, operational efficiency, and client experience.
Build and maintain cloud-native AI solutions utilizing AWS services, including Bedrock and related AI/ML technologies.
Design and implement APIs, microservices, and platform services that enable reusable and scalable AI capabilities across the enterprise.
Establish engineering best practices for AI development, model evaluation, deployment, observability, security, and responsible AI.
Collaborate with data, engineering, and architecture teams to ensure AI solutions are secure, compliant, performant, and aligned with enterprise standards.
Evaluate emerging AI technologies, frameworks, and tooling and recommend opportunities for adoption within LPL.
Provide technical leadership, mentoring, and architectural guidance to engineers and contribute to the growth of a future AI engineering team.
Present technical solutions, architecture decisions, and AI innovation opportunities to business and technology stakeholders.

Requirements

Minimum of 8 years of software engineering, AI/ML engineering, or machine learning development experience, with a proven track record of building and deploying production AI solutions in complex enterprise environments.
Strong hands-on programming expertise in Python and experience with modern AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, or similar technologies.
Experience designing, developing, and deploying Generative AI and machine learning solutions, including LLM-based applications, NLP, RAG architectures, AI agents, model serving, or related AI technologies.
Strong cloud engineering experience with AWS, Azure, or GCP, including experience deploying scalable AI/ML workloads and cloud-native applications.
Experience working in highly regulated industries such as Wealth Management, Financial Services, Banking, FinTech, Insurance, Healthcare, or similar environments with strong governance, security, risk, and compliance requirements.

Skills

Machine learning concepts including supervised learning, unsupervised learning, deep learning, NLP, recommendation systems, and predictive analytics.
Delivering AI solutions from concept through production deployment, monitoring, and optimization.
Strong software engineering fundamentals, including APIs, microservices, scalable architectures, testing, and CI/CD practices.
Partnering with product, engineering, and business stakeholders to translate business requirements into technical solutions.
Responsible AI principles, model governance, security, privacy, and risk management.
Communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
Technical leadership, mentoring, and influence across cross-functional teams.
Problem-solving, architectural design, and decision-making skills.
Building advisor-facing, customer-facing, or employee-facing AI products.
Financial Services, Wealth Management, Brokerage, Asset Management, or FinTech experience.
AWS AI services such as Bedrock, SageMaker, Textract, Comprehend, or related AI platforms.
Vector databases, embeddings, RAG, knowledge graphs, agentic AI, and LLM orchestration frameworks.
MLOps, model lifecycle management, observability, and monitoring.
Big data technologies such as Spark, Hadoop, Databricks, or large-scale data platforms.
AI governance, model validation, and regulatory compliance programs.

Location

Remote

Work Type

Full-time

Experience Level

8+ years of software engineering, AI/ML engineering, or machine learning development experience

Education Level

Master's degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field. Ph.D. preferred.

Salary/Compensations

$133,600.00 - $222,600.00

Benefits

401K matching
Health benefits
Employee stock options
Paid time off
Volunteer time off

About the Company

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace, LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans.
The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses.
At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.

Equal Opportunity

Principals only. EOE.