AVP, Principal AI Engineer

LPL Financial Corp; Fort Mill (SC); On-site; USD 134,000 - 223,000; Full time

Benefits offered by this job

401K matching

Health benefits

Employee stock options

Paid time off

Volunteer time off

More

Job summary

LPL Financial Corp seeks a hands-on AI engineering leader to design, build, and deploy production-grade AI and Generative AI solutions for advisors and business partners. You will own end-to-end AI software lifecycle and drive scalable, secure AI platforms across the firm.

Responsibilities include architecting AI-powered apps, collaborating with Wealth Management and Operations, and delivering AI-enabled tools to boost advisor productivity and client experience. Onsite in Fort Mill, SC.

Qualifications

• Minimum 8+ years in software/AI engineering, with production AI deployment experience.
• Strong Python skills with TensorFlow, PyTorch, scikit-learn, LangChain or equivalent.
• Experience delivering GenAI and ML solutions including LLM-based apps, NLP, RAG, AI agents, model serving.
• Cloud engineering with AWS/Azure/GCP; scalable AI/ML workloads and cloud-native apps.
• Experience in highly regulated industries with governance, security, risk, and compliance.

Responsibilities

• Design, develop, and deploy production-grade AI/ML solutions aligned to business objectives.
• Architect and build AI-powered applications using LLMs, generative AI, agentic workflows, and RAG architectures.
• 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 to translate requirements into scalable solutions.
• Develop and deliver AI-enabled products and tools improving advisor productivity and client experience.
• Build and maintain cloud-native AI solutions on AWS (Bedrock) and related AI/ML tech.
• Design APIs, microservices, and platform services for reusable AI capabilities enterprise-wide.
• Define best practices for AI development, including evaluation, deployment, observability, security, and responsible AI.
• Collaborate with data, engineering, and architecture teams to ensure secure, compliant AI solutions.
• Evaluate emerging AI tech and recommend adoption opportunities within LPL.
• Provide technical leadership, mentoring, and architectural guidance for the AI team.

Skills

Python

TensorFlow

PyTorch

scikit-learn

LangChain

LLMs

Generative AI

RAG architectures

AI agents

APIs

Microservices

Observability

Security

Responsible AI

Education

Master’s degree in Computer Science, Engineering, Data Science, Statistics, or related quantitative field

Tools

AWS Bedrock

SageMaker

Textract

Comprehend

Azure

GCP

Job description

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