AVP, Principal AI Engineer

LPL Financial•Charlotte, TX

About The Position

LPL Financial is seeking a highly technical and hands-on AI engineering leader to help design, build, and deploy next-generation AI solutions for our advisors and business partners. This role is primarily an individual contributor position responsible for developing production-grade AI and machine learning capabilities while partnering closely with product, engineering, data, and business teams. The ideal candidate combines deep technical expertise in AI/ML and Generative AI with the ability to influence architecture, mentor engineers, and drive adoption of AI solutions across the enterprise. This position offers the opportunity to shape LPL's AI platform strategy, build advisor-facing AI capabilities, and help 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.

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.
Deep understanding of machine learning concepts including supervised learning, unsupervised learning, deep learning, NLP, recommendation systems, and predictive analytics.
Experience 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.
Experience partnering with product, engineering, and business stakeholders to translate business requirements into technical solutions.
Knowledge of responsible AI principles, model governance, security, privacy, and risk management.
Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
Demonstrated technical leadership, mentoring, and influence across cross-functional teams.
Strong problem-solving, architectural design, and decision-making skills.

Nice To Haves

Experience building advisor-facing, customer-facing, or employee-facing AI products.
Financial Services, Wealth Management, Brokerage, Asset Management, or FinTech experience.
Experience with AWS AI services such as Bedrock, SageMaker, Textract, Comprehend, or related AI platforms.
Experience with vector databases, embeddings, RAG, knowledge graphs, agentic AI, and LLM orchestration frameworks.
Experience with MLOps, model lifecycle management, observability, and monitoring.
Experience with big data technologies such as Spark, Hadoop, Databricks, or large-scale data platforms.
Experience with AI governance, model validation, and regulatory compliance programs.
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.

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.