AVP, Principal AI Engineer

lplfinancial; Fort Mill (SC); On-site; USD 140,000 - 190,000; Full time

Job summary

LPL Financial seeks a highly technical AI engineering leader to design, build, and deploy production-grade AI/ML solutions for advisors and business partners. The role combines deep AI/ML expertise with architecture influence, mentoring, and enterprise-wide AI adoption.

The candidate will lead the end-to-end lifecycle, collaborate with product, engineering, data, and risk teams, and help establish scalable, secure, and compliant AI practices with potential leadership of a small AI engineering

Qualifications

• 8+ years of software engineering/AI/ML engineering experience
• Strong Python programming with AI/ML frameworks
• Experience deploying Generative AI and NLP solutions (LLMs, RAG)
• Cloud engineering experience with AWS/Azure/GCP and scalable AI workloads
• Experience in regulated industries with governance and security requirements

Responsibilities

• Design, develop, and deploy production-grade AI/ML solutions
• Architect and build AI-powered applications using LLMs and generative AI
• Lead end-to-end software lifecycle for AI solutions (design, test, deploy, monitor)
• Collaborate with cross-functional teams to identify high-value AI use cases
• Develop AI-enabled products and tools to improve advisor productivity and client experience
• Build cloud-native AI solutions using AWS Bedrock and related technologies
• Design APIs and microservices for reusable AI capabilities
• Establish engineering best practices for AI development, deployment, and security
• Provide technical leadership and architectural guidance
• Present AI innovations and solutions to stakeholders

Skills

Python programming

AI/ML engineering

Regulated industry experience

Architecting AI solutions

Tools

TensorFlow

PyTorch

scikit-learn

LangChain

AWS Bedrock

LLMs

Job description

Where Ambition Meets Innovation

Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you'll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals.

Job Summary

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.

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.

What are we looking for?

We're looking for strong collaborators who deliver exceptional client experiences and thrive in fast‑paced, team‑oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

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.

Core Competencies

• 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.

Knowled