Senior AI Platform Engineer (Gen AI)

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

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