AVP, Principal AI Engineer

LPL Financial is seeking a hands-on AI engineering leader to design, build, and deploy production-grade AI and Generative AI solutions for advisors and business partners.

Responsibilities

• Design, develop, and deploy production-grade AI/ML solutions aligned to business objectives and advisor experience.
• Architect and build AI-powered applications using LLMs, generative AI, agentic workflows, RAG architectures, and machine learning models.
• Own the end-to-end AI software engineering lifecycle: 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 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 on AWS, including Bedrock and related AI/ML technologies.
• Design and implement APIs, microservices, and platform services to enable reusable and scalable AI capabilities enterprise-wide.
• Define engineering best practices for AI development, including 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, then recommend adoption opportunities within LPL.
• Provide technical leadership, mentoring, and architectural guidance; contribute to the growth of an AI engineering team.
• Present technical solutions, architecture decisions, and AI innovation opportunities to business and technology stakeholders.

Requirements

• Minimum 8 years of software engineering, AI/ML engineering, or machine learning development, with a track record of building and deploying production AI in complex enterprise environments.
• Strong hands-on programming expertise in Python; experience with modern AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, or similar.
• Experience delivering Generative AI and machine learning solutions, including LLM-based applications, NLP, RAG, AI agents, model serving, or related technologies.
• Cloud engineering experience with AWS, Azure, or GCP, including deployment of scalable AI/ML workloads and cloud-native applications.
• Experience in highly regulated industries such as Wealth Management, Financial Services, Banking, FinTech, Insurance, Healthcare, or similar, with strong governance, security, risk, and compliance requirements.
• Master’s degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field.

Technologies

• Python, TensorFlow, PyTorch, scikit-learn, LangChain
• LLMs, generative AI, agentic workflows, RAG architectures, machine learning models
• AWS, Bedrock, Azure, GCP
• LLM-based applications, NLP, AI agents, model serving
• APIs, microservices, observability, security, responsible AI
• AWS AI services such as Bedrock, SageMaker, Textract, Comprehend
• Vector databases, embeddings, knowledge graphs
• LLM orchestration frameworks, agentic AI
• MLOps, model lifecycle management, monitoring
• Spark, Hadoop, Databricks, big data technologies

Core Competencies

• Deep understanding of machine learning concepts: supervised learning, unsupervised learning, deep learning, NLP, recommendation systems, and predictive analytics.
• Experience delivering AI solutions from concept to production deployment, monitoring, and optimization.
• Strong software engineering fundamentals: APIs, microservices, scalable architectures, testing, and CI/CD practices.
• Ability to partner 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.
• Communication skills to explain technical concepts to technical and non-technical audiences.
• Technical leadership with mentoring and influence across cross-functional teams.
• Problem-solving, architectural design, and decision-making skills.

Preferences

• 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 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.
• Ph.D. preferred.

Location and Compensation

• Location: Fort Mill, SC (onsite)
• Salary: USD 133,600 - 222,600 per year

Benefits

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