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.

• 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.

• 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 Tensor Flow
  , Py Torch ,
  scikit-learn
  , Lang Chain
  , 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, Fin Tech, 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.

• Python, Tensor Flow, PyTorch, scikit-learn, Lang Chain
• 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, Sage Maker, Textract, Comprehend
• Vector databases, embeddings, knowledge graphs
• LLM orchestration frameworks, agentic AI
• MLOps, model lifecycle management, monitoring
• Spark, Hadoop, Databricks, big data technologies

• 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…