AVP – Principal AI Engineer

Design, develop, and deploy production-grade AI/ML solutions supporting LPL Financial’s business objectives and advisor experience Architect and build AI-powered applications using 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 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 using AWS services, including Bedrock and related AI/ML technologies Design and implement APIs, microservices, and platform services enabling reusable and scalable AI capabilities Establish engineering best practices for AI development, model evaluation, deployment, observability, security, and responsible AI Collaborate with data, engineering, and architecture teams to ensure solutions are secure, compliant, performant, and aligned with enterprise standards Evaluate emerging AI technologies, frameworks, and tooling and recommend adoption opportunities Provide technical leadership, mentoring, and architectural guidance to engineers Present technical solutions, architecture decisions, and AI innovation opportunities to business and technology stakeholders Requirements

Minimum of 8 years of software engineering, AI/ML engineering, or machine learning development experience Proven track record of building and deploying production AI solutions in complex enterprise environments Strong hands-on programming expertise in Python Experience with TensorFlow, PyTorch, scikit-learn, LangChain, or similar AI/ML frameworks Experience designing, developing, and deploying Generative AI and machine learning solutions Experience with LLM-based applications, NLP, RAG architectures, AI agents, model serving, or related AI technologies Strong cloud engineering experience with AWS, Azure, or GCP Experience deploying 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 Understanding of 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 translating business requirements into technical solutions Knowledge of responsible AI principles, model governance, security, privacy, and risk management Demonstrated technical leadership, mentoring, and cross-functional influence 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 Core Competencies

Demonstrates expertise in designing, developing, and deploying AI/ML solutions, with a strong focus on cloud-native applications and scalable architectures. Proven ability to lead technical teams, mentor engineers, and translate business requirements into effective AI strategies. Highest-signal resume keywords

AI/ML Solution Development Cloud Engineering with AWS Python Programming Generative AI and LLM Applications Technical Leadership and Mentoring Hard Skills

Machine Learning Development API Design and Development Microservices Architecture TensorFlow PyTorch Scikit-learn NLP RAG Architectures Deep Learning Predictive Analytics Soft Skills

Cross-Functional Collaboration Technical Communication Mentoring Certifications & Qualifications

Master's Degree in Computer Science Bachelor's Degree in Computer Science Industry Keywords

Wealth Management Financial Services Banking FinTech Insurance Healthcare Responsible AI Principles Model Governance Risk Management Tools & Technologies

AWS Bedrock CI/CD Practices Cloud-Native Applications AI/ML Frameworks

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